#Preparation ## Loading Required Packages
library(png)
library(psych)
library(EFA.dimensions)
library(imager) #install XQuartz
## Loading required package: magrittr
##
## Attaching package: 'imager'
## The following object is masked from 'package:magrittr':
##
## add
## The following objects are masked from 'package:stats':
##
## convolve, spectrum
## The following object is masked from 'package:graphics':
##
## frame
## The following object is masked from 'package:base':
##
## save.image
library(corrplot)
## corrplot 0.92 loaded
library(knitr)
library(kableExtra) #choose “no” when installing
library(xtable)
##
## Attaching package: 'xtable'
## The following objects are masked from 'package:imager':
##
## display, label
library(dplyr)
##
## Attaching package: 'dplyr'
## The following object is masked from 'package:kableExtra':
##
## group_rows
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(tibble)
library(ggplot2)
##
## Attaching package: 'ggplot2'
## The following objects are masked from 'package:psych':
##
## %+%, alpha
participantResponseFiles <- list.files(path= "./03_EFA/data",pattern = "\\.csv$") #names correspond to images, one participant per row, one word per column
imageFiles <- list.files(path= "./03_EFA/images",pattern = "\\.png$")
#Clean the column names
cleanColnames <- function(data){
newNames <- gsub("^.+?\\.(.+?)\\..*$", "\\1", colnames(data))
return(newNames)
}
“A subjective method is to examine the correlation matrix. A sizable number of correlations should exceed ±.30 or EFA may be inappropriate”
correlation <- function(num,data){
return(cor(data))
}
An objective test of the factorability of the correlation matrix is Bartlett’s (1954) test of sphericity, which statistically tests the hypothesis that the correlation matrix contains ones on the diagonal and zeros on the off-diagonals. Hence, that it was generated by random data. This test should produce a statistically significant chi-square value to justify the application of EFA.
If the p-value from Bartlett’s Test of Sphericity is lower than our chosen significance level (common choices are 0.10, 0.05, and 0.01), then our dataset is suitable for a data reduction technique. (https://www.statology.org/bartletts-test-of-sphericity/)
bartlettTest <- function(num,data){
bart <- cortest.bartlett(correlation(num,data), n = nrow(data))
if(bart[2]>0.05) cat("WARNING the p value is above 0.05") else cat("The p value is below 0.05. We are good to continue.")
cat("\n\n")
print(bart)
return(bart)
}
Large sample sizes make the Bartlett test sensitive to even trivial deviations from randomness, so its results should be supplemented with a measure of sampling adequacy. The Kaiser-Meyer-Olkin (KMO; Kaiser, 1974) measure of sampling adequacy is the ratio of correlations and partial correlations that reflects the extent to which correlations are a function of the variance shared across all variables rather than the variance shared by particular pairs of variables. KMO values range from 0.00 to 1.00 and can be computed for the total correlation matrix as well as for each measured variable.
KMOTest <- function(num,data){
kmo <- KMO(data)
cat(paste("The overall measure of sampling adequacy is: ",kmo[1]))
cat("\n\n")
if(kmo[1]<.7) cat("WARNING the sampling adequacy has dropped below 0.7") else cat("The sampling adequacy is above 0.7. We are generally good.")
cat("\n\n")
return(kmo)
}
Measurement specialists have conducted simulation studies and concluded that parallel analysis and MAP are the most accurate empirical estimates of the number of factors to retain and that scree is a useful subjective adjunct to the empirical estimates. Unfortunately, no method has been found to be correct in all situations, so it is necessary to employ multiple methods and carefully judge each plausible solution to identify the most appropriate factor solution.
parallelAnalysis <- function(num,data){
cairo_pdf(paste(paste("results/ScreePlot-Image_",num,sep=""),'.pdf'), width=8, height=4)
parallel <- fa.parallel(correlation(num,data), n.obs=nrow(data), fa="fa", n.iter=100, main="Scree plots with parallel analysis")
nfact <- parallel$nfact
dev.off()
cat("\n\n")
return(nfact)
}
EFA <- function(num, factor, rotation,data){
efa <- fa(correlation(num,data), nfactors = factor, rotate = rotation, fm = "pa")
#print(xtable(unclass(efa$Structure)),type="html")
print(efa,sort=TRUE)
#fa.diagram(efa,cut=.4,digits=2) #I don't fint this diagram particularly useful
return(efa)
}
analyze_image <-function(num){
#First we plot the image that we are analyzing first
image <- load.image(paste("03_EFA/images/",imageFiles[[num]],sep=""))
plot(image)
cat("\n\n")
data <- read.csv(paste("03_EFA/data/",participantResponseFiles[[num]],sep=""), encoding="UTF-8")
colnames(data) <- cleanColnames(data)
#Then we go through the analysis steps. These are explained in detail above
#1. Correlation
# cat("### Correlation\n")
# corr <- correlation(num,data)
# pdf(paste(paste("generatedPlots-EFA/CorrelationMatrix-Image_",num,sep=""),'.pdf'), width=8, height=4)
# corrplot(corr, method="square",tl.col="black",title=paste("Correlation for Image ",num),number.cex = 0.5)
# dev.off()
# cat("\n\n")
#
# cat("### Bartlett’s test of sphericity\n")
# bartlettTest(num,data)
# cat("\n\n")
#
# cat("### KMO\n")
# KMOTest(num,data)
# cat("\n\n")
cat("## Scree Plot and Parallel Analysis\n")
nfact <- parallelAnalysis(num,data) #number of factors
cat("\n\n")
cat("## Exploratory Factor Analysis - 1 Factor - No Rotation\n")
efa_1factor <- EFA(num, 1, "none",data)
cat("\n\n")
#Exploratory Analyses below here
cat("## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)\n")
efa_2factors_varimax <- EFA(num, 2, "varimax",data )
cat("\n\n")
cat("## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)\n")
efa_2factors_promax <- EFA(num, 2, "promax",data )
cat("\n\n")
efa <- list(efa_1factor, efa_2factors_varimax, efa_2factors_promax, nfact)
return(efa)
}
imageCount <- length(participantResponseFiles)
# For debugging we can set the imageCount to whatever we want
#imageCount <- 1
df <- NULL
#number of factors suggested by parallel analysis
list_nfactor <- NULL
df_nfactor <- data.frame(matrix(ncol = 15, nrow = 0))
list_nfactor_column_name <- NULL
for (i in 1:imageCount){
list_df_nfactor_column_name <- c(list_nfactor_column_name, paste("image", i))
cat(paste(paste("## Image ",i),"\n"))
#efa_1factor
efa_1factor <- analyze_image(i)[[1]] #we want to create a big table with all the factor loadings so we'll save the efa results here
data <- NULL
loadings <- as.data.frame(unclass(efa_1factor$loadings))
h2 <- efa_1factor$communality
u2 <- efa_1factor$uniquenesses
com <- efa_1factor$complexity
data <- cbind(loadings, h2, u2, com)
data <- tibble::rownames_to_column(data,"terms")
data <- data %>%
mutate_if(is.numeric, round, digits=2)
data <- data %>% mutate_at(vars(com), funs(round(., 1)))
write.table(data, paste("results/efa_1factor_image",i,".tsv",sep=""),row.names=FALSE,sep='\t') #create factor loading table
#efa_2factors_varimax
efa_2factors_varimax <- analyze_image(i)[[2]]
data <- NULL
loadings <- as.data.frame(unclass(efa_2factors_varimax$loadings))
h2 <- efa_2factors_varimax$communality
u2 <- efa_2factors_varimax$uniquenesses
com <- efa_2factors_varimax$complexity
data <- cbind(loadings, h2, u2, com)
data <- tibble::rownames_to_column(data,"terms")
data <- data %>%
mutate_if(is.numeric, round, digits=2)
data <- data %>% mutate_at(vars(com), funs(round(., 1)))
write.table(data, paste("results/efa_2factors_varimax_image",i,".tsv",sep=""),row.names=FALSE,sep='\t')
#efa_2factors_promax
efa_2factors_promax <- analyze_image(i)[[3]]
data <- NULL
loadings <- as.data.frame(unclass(efa_2factors_promax$loadings))
h2 <- efa_2factors_promax$communality
u2 <- efa_2factors_promax$uniquenesses
com <- efa_2factors_promax$complexity
data <- cbind(loadings, h2, u2, com)
data <- tibble::rownames_to_column(data,"terms")
data <- data %>%
mutate_if(is.numeric, round, digits=2)
data <- data %>% mutate_at(vars(com), funs(round(., 1)))
write.table(data, paste("results/efa_2factors_promax_image",i,".tsv",sep=""),row.names=FALSE,sep='\t')
#number of factors
nfact <- analyze_image(i)[[4]]
list_nfactor <- c(list_nfactor, nfact)
efa_1factor <- analyze_image(i)[[1]]
if(i == 1){
df <- as.data.frame(unclass(efa_1factor$loadings))
colnames(df) <- c(paste("PA1 Image ",i))
df <- tibble::rownames_to_column(df,"terms")
}
else{
dftemp <- as.data.frame(unclass(efa_1factor$loadings))
colnames(dftemp) <- c(paste("PA1 Image ",i))
dftemp <- tibble::rownames_to_column(dftemp,"terms")
df <- merge(df,dftemp,by="terms")
}
}
## ## Image 1
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.91 0.820 0.18 1
## nice 22 0.90 0.818 0.18 1
## enjoyable 13 0.87 0.764 0.24 1
## delightful 10 0.86 0.731 0.27 1
## pleasing 24 0.85 0.721 0.28 1
## appealing 1 0.85 0.719 0.28 1
## pretty 25 0.85 0.716 0.28 1
## lovely 20 0.85 0.716 0.28 1
## beautiful 5 0.84 0.707 0.29 1
## attractive 3 0.84 0.707 0.29 1
## elegant 11 0.83 0.696 0.30 1
## inviting 18 0.83 0.694 0.31 1
## exciting 14 0.79 0.625 0.38 1
## engaging 12 0.79 0.624 0.38 1
## harmonious 16 0.79 0.621 0.38 1
## tasteful 30 0.78 0.615 0.38 1
## satisfying 28 0.77 0.597 0.40 1
## wellDesigned 31 0.76 0.578 0.42 1
## motivating 21 0.74 0.549 0.45 1
## clean 6 0.73 0.527 0.47 1
## interesting 17 0.70 0.495 0.51 1
## balanced 4 0.69 0.480 0.52 1
## sophisticated 29 0.68 0.467 0.53 1
## fascinating 15 0.68 0.458 0.54 1
## colorHarmonious 8 0.65 0.427 0.57 1
## professional 26 0.63 0.400 0.60 1
## organized 23 0.59 0.348 0.65 1
## creative 9 0.53 0.284 0.72 1
## artistic 2 0.52 0.268 0.73 1
## cluttered 7 0.30 0.093 0.91 1
## provoking 27 0.17 0.029 0.97 1
##
## PA1
## SS loadings 17.29
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 434 and the objective function was 5.64
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.79 0.20 0.671 0.33 1.1
## balanced 4 0.78 0.17 0.630 0.37 1.1
## organized 23 0.72 0.07 0.530 0.47 1.0
## wellDesigned 31 0.69 0.37 0.609 0.39 1.5
## harmonious 16 0.69 0.41 0.640 0.36 1.6
## nice 22 0.68 0.59 0.817 0.18 2.0
## elegant 11 0.68 0.48 0.702 0.30 1.8
## inviting 18 0.68 0.48 0.700 0.30 1.8
## professional 26 0.67 0.20 0.485 0.52 1.2
## likable 19 0.66 0.62 0.820 0.18 2.0
## delightful 10 0.64 0.56 0.730 0.27 2.0
## lovely 20 0.63 0.57 0.714 0.29 2.0
## tasteful 30 0.61 0.49 0.615 0.39 1.9
## appealing 1 0.61 0.59 0.720 0.28 2.0
## pleasing 24 0.61 0.60 0.723 0.28 2.0
## motivating 21 0.60 0.43 0.553 0.45 1.8
## beautiful 5 0.60 0.59 0.710 0.29 2.0
## attractive 3 0.60 0.59 0.710 0.29 2.0
## engaging 12 0.58 0.54 0.624 0.38 2.0
## sophisticated 29 0.55 0.41 0.468 0.53 1.9
## colorHarmonious 8 0.52 0.40 0.428 0.57 1.9
## cluttered 7 0.35 0.05 0.129 0.87 1.0
## interesting 17 0.28 0.76 0.655 0.34 1.3
## fascinating 15 0.30 0.69 0.568 0.43 1.4
## exciting 14 0.47 0.67 0.669 0.33 1.8
## enjoyable 13 0.61 0.63 0.769 0.23 2.0
## creative 9 0.17 0.62 0.416 0.58 1.2
## artistic 2 0.16 0.61 0.399 0.60 1.1
## pretty 25 0.60 0.60 0.720 0.28 2.0
## satisfying 28 0.54 0.55 0.600 0.40 2.0
## provoking 27 -0.01 0.27 0.073 0.93 1.0
##
## PA1 PA2
## SS loadings 10.49 8.10
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.92
## Multiple R square of scores with factors 0.88 0.85
## Minimum correlation of possible factor scores 0.77 0.70
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Loading required namespace: GPArotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.95 -0.19 0.671 0.33 1.1
## balanced 4 0.94 -0.22 0.630 0.37 1.1
## organized 23 0.93 -0.32 0.530 0.47 1.2
## professional 26 0.78 -0.12 0.485 0.52 1.0
## wellDesigned 31 0.71 0.09 0.609 0.39 1.0
## harmonious 16 0.68 0.15 0.640 0.36 1.1
## elegant 11 0.64 0.25 0.702 0.30 1.3
## inviting 18 0.63 0.25 0.700 0.30 1.3
## nice 22 0.58 0.39 0.817 0.18 1.8
## motivating 21 0.56 0.23 0.553 0.45 1.3
## delightful 10 0.53 0.38 0.730 0.27 1.8
## tasteful 30 0.53 0.31 0.615 0.39 1.6
## likable 19 0.53 0.44 0.820 0.18 1.9
## lovely 20 0.51 0.39 0.714 0.29 1.9
## sophisticated 29 0.49 0.24 0.468 0.53 1.4
## appealing 1 0.47 0.44 0.720 0.28 2.0
## pleasing 24 0.47 0.45 0.723 0.28 2.0
## colorHarmonious 8 0.47 0.23 0.428 0.57 1.5
## engaging 12 0.46 0.39 0.624 0.38 1.9
## beautiful 5 0.46 0.45 0.710 0.29 2.0
## attractive 3 0.46 0.45 0.710 0.29 2.0
## cluttered 7 0.44 -0.13 0.129 0.87 1.2
## interesting 17 -0.06 0.85 0.655 0.34 1.0
## fascinating 15 0.01 0.74 0.568 0.43 1.0
## creative 9 -0.12 0.73 0.416 0.58 1.1
## artistic 2 -0.13 0.72 0.399 0.60 1.1
## exciting 14 0.24 0.63 0.669 0.33 1.3
## enjoyable 13 0.46 0.49 0.769 0.23 2.0
## pretty 25 0.45 0.46 0.720 0.28 2.0
## satisfying 28 0.41 0.42 0.600 0.40 2.0
## provoking 27 -0.17 0.37 0.073 0.93 1.4
##
## PA1 PA2
## SS loadings 11.05 7.54
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.60
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.87
## Warning: `funs()` was deprecated in dplyr 0.8.0.
## Please use a list of either functions or lambdas:
##
## # Simple named list:
## list(mean = mean, median = median)
##
## # Auto named with `tibble::lst()`:
## tibble::lst(mean, median)
##
## # Using lambdas
## list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.91 0.820 0.18 1
## nice 22 0.90 0.818 0.18 1
## enjoyable 13 0.87 0.764 0.24 1
## delightful 10 0.86 0.731 0.27 1
## pleasing 24 0.85 0.721 0.28 1
## appealing 1 0.85 0.719 0.28 1
## pretty 25 0.85 0.716 0.28 1
## lovely 20 0.85 0.716 0.28 1
## beautiful 5 0.84 0.707 0.29 1
## attractive 3 0.84 0.707 0.29 1
## elegant 11 0.83 0.696 0.30 1
## inviting 18 0.83 0.694 0.31 1
## exciting 14 0.79 0.625 0.38 1
## engaging 12 0.79 0.624 0.38 1
## harmonious 16 0.79 0.621 0.38 1
## tasteful 30 0.78 0.615 0.38 1
## satisfying 28 0.77 0.597 0.40 1
## wellDesigned 31 0.76 0.578 0.42 1
## motivating 21 0.74 0.549 0.45 1
## clean 6 0.73 0.527 0.47 1
## interesting 17 0.70 0.495 0.51 1
## balanced 4 0.69 0.480 0.52 1
## sophisticated 29 0.68 0.467 0.53 1
## fascinating 15 0.68 0.458 0.54 1
## colorHarmonious 8 0.65 0.427 0.57 1
## professional 26 0.63 0.400 0.60 1
## organized 23 0.59 0.348 0.65 1
## creative 9 0.53 0.284 0.72 1
## artistic 2 0.52 0.268 0.73 1
## cluttered 7 0.30 0.093 0.91 1
## provoking 27 0.17 0.029 0.97 1
##
## PA1
## SS loadings 17.29
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 434 and the objective function was 5.64
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.79 0.20 0.671 0.33 1.1
## balanced 4 0.78 0.17 0.630 0.37 1.1
## organized 23 0.72 0.07 0.530 0.47 1.0
## wellDesigned 31 0.69 0.37 0.609 0.39 1.5
## harmonious 16 0.69 0.41 0.640 0.36 1.6
## nice 22 0.68 0.59 0.817 0.18 2.0
## elegant 11 0.68 0.48 0.702 0.30 1.8
## inviting 18 0.68 0.48 0.700 0.30 1.8
## professional 26 0.67 0.20 0.485 0.52 1.2
## likable 19 0.66 0.62 0.820 0.18 2.0
## delightful 10 0.64 0.56 0.730 0.27 2.0
## lovely 20 0.63 0.57 0.714 0.29 2.0
## tasteful 30 0.61 0.49 0.615 0.39 1.9
## appealing 1 0.61 0.59 0.720 0.28 2.0
## pleasing 24 0.61 0.60 0.723 0.28 2.0
## motivating 21 0.60 0.43 0.553 0.45 1.8
## beautiful 5 0.60 0.59 0.710 0.29 2.0
## attractive 3 0.60 0.59 0.710 0.29 2.0
## engaging 12 0.58 0.54 0.624 0.38 2.0
## sophisticated 29 0.55 0.41 0.468 0.53 1.9
## colorHarmonious 8 0.52 0.40 0.428 0.57 1.9
## cluttered 7 0.35 0.05 0.129 0.87 1.0
## interesting 17 0.28 0.76 0.655 0.34 1.3
## fascinating 15 0.30 0.69 0.568 0.43 1.4
## exciting 14 0.47 0.67 0.669 0.33 1.8
## enjoyable 13 0.61 0.63 0.769 0.23 2.0
## creative 9 0.17 0.62 0.416 0.58 1.2
## artistic 2 0.16 0.61 0.399 0.60 1.1
## pretty 25 0.60 0.60 0.720 0.28 2.0
## satisfying 28 0.54 0.55 0.600 0.40 2.0
## provoking 27 -0.01 0.27 0.073 0.93 1.0
##
## PA1 PA2
## SS loadings 10.49 8.10
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.92
## Multiple R square of scores with factors 0.88 0.85
## Minimum correlation of possible factor scores 0.77 0.70
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.95 -0.19 0.671 0.33 1.1
## balanced 4 0.94 -0.22 0.630 0.37 1.1
## organized 23 0.93 -0.32 0.530 0.47 1.2
## professional 26 0.78 -0.12 0.485 0.52 1.0
## wellDesigned 31 0.71 0.09 0.609 0.39 1.0
## harmonious 16 0.68 0.15 0.640 0.36 1.1
## elegant 11 0.64 0.25 0.702 0.30 1.3
## inviting 18 0.63 0.25 0.700 0.30 1.3
## nice 22 0.58 0.39 0.817 0.18 1.8
## motivating 21 0.56 0.23 0.553 0.45 1.3
## delightful 10 0.53 0.38 0.730 0.27 1.8
## tasteful 30 0.53 0.31 0.615 0.39 1.6
## likable 19 0.53 0.44 0.820 0.18 1.9
## lovely 20 0.51 0.39 0.714 0.29 1.9
## sophisticated 29 0.49 0.24 0.468 0.53 1.4
## appealing 1 0.47 0.44 0.720 0.28 2.0
## pleasing 24 0.47 0.45 0.723 0.28 2.0
## colorHarmonious 8 0.47 0.23 0.428 0.57 1.5
## engaging 12 0.46 0.39 0.624 0.38 1.9
## beautiful 5 0.46 0.45 0.710 0.29 2.0
## attractive 3 0.46 0.45 0.710 0.29 2.0
## cluttered 7 0.44 -0.13 0.129 0.87 1.2
## interesting 17 -0.06 0.85 0.655 0.34 1.0
## fascinating 15 0.01 0.74 0.568 0.43 1.0
## creative 9 -0.12 0.73 0.416 0.58 1.1
## artistic 2 -0.13 0.72 0.399 0.60 1.1
## exciting 14 0.24 0.63 0.669 0.33 1.3
## enjoyable 13 0.46 0.49 0.769 0.23 2.0
## pretty 25 0.45 0.46 0.720 0.28 2.0
## satisfying 28 0.41 0.42 0.600 0.40 2.0
## provoking 27 -0.17 0.37 0.073 0.93 1.4
##
## PA1 PA2
## SS loadings 11.05 7.54
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.60
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.87
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.91 0.820 0.18 1
## nice 22 0.90 0.818 0.18 1
## enjoyable 13 0.87 0.764 0.24 1
## delightful 10 0.86 0.731 0.27 1
## pleasing 24 0.85 0.721 0.28 1
## appealing 1 0.85 0.719 0.28 1
## pretty 25 0.85 0.716 0.28 1
## lovely 20 0.85 0.716 0.28 1
## beautiful 5 0.84 0.707 0.29 1
## attractive 3 0.84 0.707 0.29 1
## elegant 11 0.83 0.696 0.30 1
## inviting 18 0.83 0.694 0.31 1
## exciting 14 0.79 0.625 0.38 1
## engaging 12 0.79 0.624 0.38 1
## harmonious 16 0.79 0.621 0.38 1
## tasteful 30 0.78 0.615 0.38 1
## satisfying 28 0.77 0.597 0.40 1
## wellDesigned 31 0.76 0.578 0.42 1
## motivating 21 0.74 0.549 0.45 1
## clean 6 0.73 0.527 0.47 1
## interesting 17 0.70 0.495 0.51 1
## balanced 4 0.69 0.480 0.52 1
## sophisticated 29 0.68 0.467 0.53 1
## fascinating 15 0.68 0.458 0.54 1
## colorHarmonious 8 0.65 0.427 0.57 1
## professional 26 0.63 0.400 0.60 1
## organized 23 0.59 0.348 0.65 1
## creative 9 0.53 0.284 0.72 1
## artistic 2 0.52 0.268 0.73 1
## cluttered 7 0.30 0.093 0.91 1
## provoking 27 0.17 0.029 0.97 1
##
## PA1
## SS loadings 17.29
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 434 and the objective function was 5.64
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.79 0.20 0.671 0.33 1.1
## balanced 4 0.78 0.17 0.630 0.37 1.1
## organized 23 0.72 0.07 0.530 0.47 1.0
## wellDesigned 31 0.69 0.37 0.609 0.39 1.5
## harmonious 16 0.69 0.41 0.640 0.36 1.6
## nice 22 0.68 0.59 0.817 0.18 2.0
## elegant 11 0.68 0.48 0.702 0.30 1.8
## inviting 18 0.68 0.48 0.700 0.30 1.8
## professional 26 0.67 0.20 0.485 0.52 1.2
## likable 19 0.66 0.62 0.820 0.18 2.0
## delightful 10 0.64 0.56 0.730 0.27 2.0
## lovely 20 0.63 0.57 0.714 0.29 2.0
## tasteful 30 0.61 0.49 0.615 0.39 1.9
## appealing 1 0.61 0.59 0.720 0.28 2.0
## pleasing 24 0.61 0.60 0.723 0.28 2.0
## motivating 21 0.60 0.43 0.553 0.45 1.8
## beautiful 5 0.60 0.59 0.710 0.29 2.0
## attractive 3 0.60 0.59 0.710 0.29 2.0
## engaging 12 0.58 0.54 0.624 0.38 2.0
## sophisticated 29 0.55 0.41 0.468 0.53 1.9
## colorHarmonious 8 0.52 0.40 0.428 0.57 1.9
## cluttered 7 0.35 0.05 0.129 0.87 1.0
## interesting 17 0.28 0.76 0.655 0.34 1.3
## fascinating 15 0.30 0.69 0.568 0.43 1.4
## exciting 14 0.47 0.67 0.669 0.33 1.8
## enjoyable 13 0.61 0.63 0.769 0.23 2.0
## creative 9 0.17 0.62 0.416 0.58 1.2
## artistic 2 0.16 0.61 0.399 0.60 1.1
## pretty 25 0.60 0.60 0.720 0.28 2.0
## satisfying 28 0.54 0.55 0.600 0.40 2.0
## provoking 27 -0.01 0.27 0.073 0.93 1.0
##
## PA1 PA2
## SS loadings 10.49 8.10
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.92
## Multiple R square of scores with factors 0.88 0.85
## Minimum correlation of possible factor scores 0.77 0.70
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.95 -0.19 0.671 0.33 1.1
## balanced 4 0.94 -0.22 0.630 0.37 1.1
## organized 23 0.93 -0.32 0.530 0.47 1.2
## professional 26 0.78 -0.12 0.485 0.52 1.0
## wellDesigned 31 0.71 0.09 0.609 0.39 1.0
## harmonious 16 0.68 0.15 0.640 0.36 1.1
## elegant 11 0.64 0.25 0.702 0.30 1.3
## inviting 18 0.63 0.25 0.700 0.30 1.3
## nice 22 0.58 0.39 0.817 0.18 1.8
## motivating 21 0.56 0.23 0.553 0.45 1.3
## delightful 10 0.53 0.38 0.730 0.27 1.8
## tasteful 30 0.53 0.31 0.615 0.39 1.6
## likable 19 0.53 0.44 0.820 0.18 1.9
## lovely 20 0.51 0.39 0.714 0.29 1.9
## sophisticated 29 0.49 0.24 0.468 0.53 1.4
## appealing 1 0.47 0.44 0.720 0.28 2.0
## pleasing 24 0.47 0.45 0.723 0.28 2.0
## colorHarmonious 8 0.47 0.23 0.428 0.57 1.5
## engaging 12 0.46 0.39 0.624 0.38 1.9
## beautiful 5 0.46 0.45 0.710 0.29 2.0
## attractive 3 0.46 0.45 0.710 0.29 2.0
## cluttered 7 0.44 -0.13 0.129 0.87 1.2
## interesting 17 -0.06 0.85 0.655 0.34 1.0
## fascinating 15 0.01 0.74 0.568 0.43 1.0
## creative 9 -0.12 0.73 0.416 0.58 1.1
## artistic 2 -0.13 0.72 0.399 0.60 1.1
## exciting 14 0.24 0.63 0.669 0.33 1.3
## enjoyable 13 0.46 0.49 0.769 0.23 2.0
## pretty 25 0.45 0.46 0.720 0.28 2.0
## satisfying 28 0.41 0.42 0.600 0.40 2.0
## provoking 27 -0.17 0.37 0.073 0.93 1.4
##
## PA1 PA2
## SS loadings 11.05 7.54
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.60
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.87
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.91 0.820 0.18 1
## nice 22 0.90 0.818 0.18 1
## enjoyable 13 0.87 0.764 0.24 1
## delightful 10 0.86 0.731 0.27 1
## pleasing 24 0.85 0.721 0.28 1
## appealing 1 0.85 0.719 0.28 1
## pretty 25 0.85 0.716 0.28 1
## lovely 20 0.85 0.716 0.28 1
## beautiful 5 0.84 0.707 0.29 1
## attractive 3 0.84 0.707 0.29 1
## elegant 11 0.83 0.696 0.30 1
## inviting 18 0.83 0.694 0.31 1
## exciting 14 0.79 0.625 0.38 1
## engaging 12 0.79 0.624 0.38 1
## harmonious 16 0.79 0.621 0.38 1
## tasteful 30 0.78 0.615 0.38 1
## satisfying 28 0.77 0.597 0.40 1
## wellDesigned 31 0.76 0.578 0.42 1
## motivating 21 0.74 0.549 0.45 1
## clean 6 0.73 0.527 0.47 1
## interesting 17 0.70 0.495 0.51 1
## balanced 4 0.69 0.480 0.52 1
## sophisticated 29 0.68 0.467 0.53 1
## fascinating 15 0.68 0.458 0.54 1
## colorHarmonious 8 0.65 0.427 0.57 1
## professional 26 0.63 0.400 0.60 1
## organized 23 0.59 0.348 0.65 1
## creative 9 0.53 0.284 0.72 1
## artistic 2 0.52 0.268 0.73 1
## cluttered 7 0.30 0.093 0.91 1
## provoking 27 0.17 0.029 0.97 1
##
## PA1
## SS loadings 17.29
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 434 and the objective function was 5.64
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.79 0.20 0.671 0.33 1.1
## balanced 4 0.78 0.17 0.630 0.37 1.1
## organized 23 0.72 0.07 0.530 0.47 1.0
## wellDesigned 31 0.69 0.37 0.609 0.39 1.5
## harmonious 16 0.69 0.41 0.640 0.36 1.6
## nice 22 0.68 0.59 0.817 0.18 2.0
## elegant 11 0.68 0.48 0.702 0.30 1.8
## inviting 18 0.68 0.48 0.700 0.30 1.8
## professional 26 0.67 0.20 0.485 0.52 1.2
## likable 19 0.66 0.62 0.820 0.18 2.0
## delightful 10 0.64 0.56 0.730 0.27 2.0
## lovely 20 0.63 0.57 0.714 0.29 2.0
## tasteful 30 0.61 0.49 0.615 0.39 1.9
## appealing 1 0.61 0.59 0.720 0.28 2.0
## pleasing 24 0.61 0.60 0.723 0.28 2.0
## motivating 21 0.60 0.43 0.553 0.45 1.8
## beautiful 5 0.60 0.59 0.710 0.29 2.0
## attractive 3 0.60 0.59 0.710 0.29 2.0
## engaging 12 0.58 0.54 0.624 0.38 2.0
## sophisticated 29 0.55 0.41 0.468 0.53 1.9
## colorHarmonious 8 0.52 0.40 0.428 0.57 1.9
## cluttered 7 0.35 0.05 0.129 0.87 1.0
## interesting 17 0.28 0.76 0.655 0.34 1.3
## fascinating 15 0.30 0.69 0.568 0.43 1.4
## exciting 14 0.47 0.67 0.669 0.33 1.8
## enjoyable 13 0.61 0.63 0.769 0.23 2.0
## creative 9 0.17 0.62 0.416 0.58 1.2
## artistic 2 0.16 0.61 0.399 0.60 1.1
## pretty 25 0.60 0.60 0.720 0.28 2.0
## satisfying 28 0.54 0.55 0.600 0.40 2.0
## provoking 27 -0.01 0.27 0.073 0.93 1.0
##
## PA1 PA2
## SS loadings 10.49 8.10
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.92
## Multiple R square of scores with factors 0.88 0.85
## Minimum correlation of possible factor scores 0.77 0.70
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.95 -0.19 0.671 0.33 1.1
## balanced 4 0.94 -0.22 0.630 0.37 1.1
## organized 23 0.93 -0.32 0.530 0.47 1.2
## professional 26 0.78 -0.12 0.485 0.52 1.0
## wellDesigned 31 0.71 0.09 0.609 0.39 1.0
## harmonious 16 0.68 0.15 0.640 0.36 1.1
## elegant 11 0.64 0.25 0.702 0.30 1.3
## inviting 18 0.63 0.25 0.700 0.30 1.3
## nice 22 0.58 0.39 0.817 0.18 1.8
## motivating 21 0.56 0.23 0.553 0.45 1.3
## delightful 10 0.53 0.38 0.730 0.27 1.8
## tasteful 30 0.53 0.31 0.615 0.39 1.6
## likable 19 0.53 0.44 0.820 0.18 1.9
## lovely 20 0.51 0.39 0.714 0.29 1.9
## sophisticated 29 0.49 0.24 0.468 0.53 1.4
## appealing 1 0.47 0.44 0.720 0.28 2.0
## pleasing 24 0.47 0.45 0.723 0.28 2.0
## colorHarmonious 8 0.47 0.23 0.428 0.57 1.5
## engaging 12 0.46 0.39 0.624 0.38 1.9
## beautiful 5 0.46 0.45 0.710 0.29 2.0
## attractive 3 0.46 0.45 0.710 0.29 2.0
## cluttered 7 0.44 -0.13 0.129 0.87 1.2
## interesting 17 -0.06 0.85 0.655 0.34 1.0
## fascinating 15 0.01 0.74 0.568 0.43 1.0
## creative 9 -0.12 0.73 0.416 0.58 1.1
## artistic 2 -0.13 0.72 0.399 0.60 1.1
## exciting 14 0.24 0.63 0.669 0.33 1.3
## enjoyable 13 0.46 0.49 0.769 0.23 2.0
## pretty 25 0.45 0.46 0.720 0.28 2.0
## satisfying 28 0.41 0.42 0.600 0.40 2.0
## provoking 27 -0.17 0.37 0.073 0.93 1.4
##
## PA1 PA2
## SS loadings 11.05 7.54
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.60
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.87
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.91 0.820 0.18 1
## nice 22 0.90 0.818 0.18 1
## enjoyable 13 0.87 0.764 0.24 1
## delightful 10 0.86 0.731 0.27 1
## pleasing 24 0.85 0.721 0.28 1
## appealing 1 0.85 0.719 0.28 1
## pretty 25 0.85 0.716 0.28 1
## lovely 20 0.85 0.716 0.28 1
## beautiful 5 0.84 0.707 0.29 1
## attractive 3 0.84 0.707 0.29 1
## elegant 11 0.83 0.696 0.30 1
## inviting 18 0.83 0.694 0.31 1
## exciting 14 0.79 0.625 0.38 1
## engaging 12 0.79 0.624 0.38 1
## harmonious 16 0.79 0.621 0.38 1
## tasteful 30 0.78 0.615 0.38 1
## satisfying 28 0.77 0.597 0.40 1
## wellDesigned 31 0.76 0.578 0.42 1
## motivating 21 0.74 0.549 0.45 1
## clean 6 0.73 0.527 0.47 1
## interesting 17 0.70 0.495 0.51 1
## balanced 4 0.69 0.480 0.52 1
## sophisticated 29 0.68 0.467 0.53 1
## fascinating 15 0.68 0.458 0.54 1
## colorHarmonious 8 0.65 0.427 0.57 1
## professional 26 0.63 0.400 0.60 1
## organized 23 0.59 0.348 0.65 1
## creative 9 0.53 0.284 0.72 1
## artistic 2 0.52 0.268 0.73 1
## cluttered 7 0.30 0.093 0.91 1
## provoking 27 0.17 0.029 0.97 1
##
## PA1
## SS loadings 17.29
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 434 and the objective function was 5.64
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.79 0.20 0.671 0.33 1.1
## balanced 4 0.78 0.17 0.630 0.37 1.1
## organized 23 0.72 0.07 0.530 0.47 1.0
## wellDesigned 31 0.69 0.37 0.609 0.39 1.5
## harmonious 16 0.69 0.41 0.640 0.36 1.6
## nice 22 0.68 0.59 0.817 0.18 2.0
## elegant 11 0.68 0.48 0.702 0.30 1.8
## inviting 18 0.68 0.48 0.700 0.30 1.8
## professional 26 0.67 0.20 0.485 0.52 1.2
## likable 19 0.66 0.62 0.820 0.18 2.0
## delightful 10 0.64 0.56 0.730 0.27 2.0
## lovely 20 0.63 0.57 0.714 0.29 2.0
## tasteful 30 0.61 0.49 0.615 0.39 1.9
## appealing 1 0.61 0.59 0.720 0.28 2.0
## pleasing 24 0.61 0.60 0.723 0.28 2.0
## motivating 21 0.60 0.43 0.553 0.45 1.8
## beautiful 5 0.60 0.59 0.710 0.29 2.0
## attractive 3 0.60 0.59 0.710 0.29 2.0
## engaging 12 0.58 0.54 0.624 0.38 2.0
## sophisticated 29 0.55 0.41 0.468 0.53 1.9
## colorHarmonious 8 0.52 0.40 0.428 0.57 1.9
## cluttered 7 0.35 0.05 0.129 0.87 1.0
## interesting 17 0.28 0.76 0.655 0.34 1.3
## fascinating 15 0.30 0.69 0.568 0.43 1.4
## exciting 14 0.47 0.67 0.669 0.33 1.8
## enjoyable 13 0.61 0.63 0.769 0.23 2.0
## creative 9 0.17 0.62 0.416 0.58 1.2
## artistic 2 0.16 0.61 0.399 0.60 1.1
## pretty 25 0.60 0.60 0.720 0.28 2.0
## satisfying 28 0.54 0.55 0.600 0.40 2.0
## provoking 27 -0.01 0.27 0.073 0.93 1.0
##
## PA1 PA2
## SS loadings 10.49 8.10
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.92
## Multiple R square of scores with factors 0.88 0.85
## Minimum correlation of possible factor scores 0.77 0.70
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.95 -0.19 0.671 0.33 1.1
## balanced 4 0.94 -0.22 0.630 0.37 1.1
## organized 23 0.93 -0.32 0.530 0.47 1.2
## professional 26 0.78 -0.12 0.485 0.52 1.0
## wellDesigned 31 0.71 0.09 0.609 0.39 1.0
## harmonious 16 0.68 0.15 0.640 0.36 1.1
## elegant 11 0.64 0.25 0.702 0.30 1.3
## inviting 18 0.63 0.25 0.700 0.30 1.3
## nice 22 0.58 0.39 0.817 0.18 1.8
## motivating 21 0.56 0.23 0.553 0.45 1.3
## delightful 10 0.53 0.38 0.730 0.27 1.8
## tasteful 30 0.53 0.31 0.615 0.39 1.6
## likable 19 0.53 0.44 0.820 0.18 1.9
## lovely 20 0.51 0.39 0.714 0.29 1.9
## sophisticated 29 0.49 0.24 0.468 0.53 1.4
## appealing 1 0.47 0.44 0.720 0.28 2.0
## pleasing 24 0.47 0.45 0.723 0.28 2.0
## colorHarmonious 8 0.47 0.23 0.428 0.57 1.5
## engaging 12 0.46 0.39 0.624 0.38 1.9
## beautiful 5 0.46 0.45 0.710 0.29 2.0
## attractive 3 0.46 0.45 0.710 0.29 2.0
## cluttered 7 0.44 -0.13 0.129 0.87 1.2
## interesting 17 -0.06 0.85 0.655 0.34 1.0
## fascinating 15 0.01 0.74 0.568 0.43 1.0
## creative 9 -0.12 0.73 0.416 0.58 1.1
## artistic 2 -0.13 0.72 0.399 0.60 1.1
## exciting 14 0.24 0.63 0.669 0.33 1.3
## enjoyable 13 0.46 0.49 0.769 0.23 2.0
## pretty 25 0.45 0.46 0.720 0.28 2.0
## satisfying 28 0.41 0.42 0.600 0.40 2.0
## provoking 27 -0.17 0.37 0.073 0.93 1.4
##
## PA1 PA2
## SS loadings 11.05 7.54
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.60
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.91
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.87
##
##
## ## Image 2
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.81 0.653 0.35 1
## pleasing 24 0.80 0.646 0.35 1
## appealing 1 0.80 0.644 0.36 1
## likable 19 0.79 0.619 0.38 1
## enjoyable 13 0.78 0.609 0.39 1
## attractive 3 0.78 0.601 0.40 1
## beautiful 5 0.77 0.587 0.41 1
## elegant 11 0.76 0.572 0.43 1
## pretty 25 0.76 0.571 0.43 1
## lovely 20 0.75 0.560 0.44 1
## delightful 10 0.74 0.553 0.45 1
## inviting 18 0.74 0.541 0.46 1
## satisfying 28 0.73 0.540 0.46 1
## wellDesigned 31 0.71 0.499 0.50 1
## interesting 17 0.70 0.494 0.51 1
## engaging 12 0.70 0.490 0.51 1
## clean 6 0.70 0.484 0.52 1
## harmonious 16 0.69 0.477 0.52 1
## professional 26 0.67 0.450 0.55 1
## exciting 14 0.66 0.440 0.56 1
## motivating 21 0.65 0.424 0.58 1
## tasteful 30 0.64 0.414 0.59 1
## fascinating 15 0.64 0.413 0.59 1
## balanced 4 0.63 0.394 0.61 1
## sophisticated 29 0.63 0.391 0.61 1
## organized 23 0.61 0.378 0.62 1
## colorHarmonious 8 0.59 0.349 0.65 1
## artistic 2 0.49 0.241 0.76 1
## creative 9 0.49 0.240 0.76 1
## cluttered 7 -0.33 0.108 0.89 1
## provoking 27 0.20 0.039 0.96 1
##
## PA1
## SS loadings 14.42
## Proportion Var 0.47
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 434 and the objective function was 6.68
##
## The root mean square of the residuals (RMSR) is 0.09
## The df corrected root mean square of the residuals is 0.09
##
## Fit based upon off diagonal values = 0.97
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.98
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.94
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.79 0.05 0.63 0.37 1.0
## clean 6 0.77 0.19 0.63 0.37 1.1
## professional 26 0.75 0.17 0.60 0.40 1.1
## nice 22 0.75 0.37 0.70 0.30 1.5
## balanced 4 0.73 0.14 0.55 0.45 1.1
## likable 19 0.72 0.38 0.66 0.34 1.5
## wellDesigned 31 0.68 0.30 0.55 0.45 1.4
## harmonious 16 0.68 0.28 0.54 0.46 1.3
## colorHarmonious 8 0.67 0.14 0.47 0.53 1.1
## pleasing 24 0.67 0.46 0.65 0.35 1.8
## appealing 1 0.61 0.52 0.64 0.36 1.9
## satisfying 28 0.61 0.42 0.55 0.45 1.8
## enjoyable 13 0.58 0.51 0.61 0.39 2.0
## tasteful 30 0.58 0.32 0.43 0.57 1.6
## attractive 3 0.57 0.52 0.60 0.40 2.0
## cluttered 7 -0.46 0.02 0.21 0.79 1.0
## exciting 14 0.20 0.79 0.66 0.34 1.1
## fascinating 15 0.21 0.74 0.59 0.41 1.2
## motivating 21 0.27 0.69 0.54 0.46 1.3
## artistic 2 0.06 0.68 0.47 0.53 1.0
## creative 9 0.07 0.67 0.45 0.55 1.0
## delightful 10 0.41 0.66 0.61 0.39 1.7
## inviting 18 0.41 0.65 0.59 0.41 1.7
## beautiful 5 0.46 0.64 0.61 0.39 1.8
## sophisticated 29 0.30 0.60 0.45 0.55 1.5
## engaging 12 0.40 0.60 0.52 0.48 1.8
## lovely 20 0.47 0.59 0.58 0.42 1.9
## elegant 11 0.51 0.56 0.58 0.42 2.0
## pretty 25 0.53 0.54 0.57 0.43 2.0
## interesting 17 0.48 0.52 0.50 0.50 2.0
## provoking 27 -0.06 0.37 0.14 0.86 1.1
##
## PA1 PA2
## SS loadings 9.14 7.73
## Proportion Var 0.29 0.25
## Cumulative Var 0.29 0.54
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.95
## Multiple R square of scores with factors 0.92 0.90
## Minimum correlation of possible factor scores 0.84 0.80
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.94 -0.28 0.63 0.37 1.2
## clean 6 0.86 -0.10 0.63 0.37 1.0
## professional 26 0.84 -0.12 0.60 0.40 1.0
## balanced 4 0.82 -0.15 0.55 0.45 1.1
## colorHarmonious 8 0.76 -0.12 0.47 0.53 1.1
## nice 22 0.75 0.13 0.70 0.30 1.1
## likable 19 0.70 0.15 0.66 0.34 1.1
## harmonious 16 0.70 0.05 0.54 0.46 1.0
## wellDesigned 31 0.69 0.08 0.55 0.45 1.0
## pleasing 24 0.61 0.27 0.65 0.35 1.4
## tasteful 30 0.56 0.14 0.43 0.57 1.1
## cluttered 7 -0.56 0.22 0.21 0.79 1.3
## satisfying 28 0.56 0.25 0.55 0.45 1.4
## appealing 1 0.52 0.37 0.64 0.36 1.8
## enjoyable 13 0.49 0.37 0.61 0.39 1.9
## attractive 3 0.47 0.38 0.60 0.40 1.9
## exciting 14 -0.10 0.87 0.66 0.34 1.0
## fascinating 15 -0.06 0.81 0.59 0.41 1.0
## artistic 2 -0.22 0.80 0.47 0.53 1.2
## creative 9 -0.20 0.78 0.45 0.55 1.1
## motivating 21 0.03 0.72 0.54 0.46 1.0
## delightful 10 0.20 0.63 0.61 0.39 1.2
## inviting 18 0.22 0.61 0.59 0.41 1.3
## sophisticated 29 0.11 0.60 0.45 0.55 1.1
## beautiful 5 0.28 0.57 0.61 0.39 1.5
## engaging 12 0.23 0.55 0.52 0.48 1.3
## lovely 20 0.32 0.52 0.58 0.42 1.7
## provoking 27 -0.23 0.47 0.14 0.86 1.5
## elegant 11 0.38 0.46 0.58 0.42 1.9
## interesting 17 0.36 0.42 0.50 0.50 1.9
## pretty 25 0.42 0.42 0.57 0.43 2.0
##
## PA1 PA2
## SS loadings 9.32 7.54
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.63
## PA2 0.63 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.81 0.653 0.35 1
## pleasing 24 0.80 0.646 0.35 1
## appealing 1 0.80 0.644 0.36 1
## likable 19 0.79 0.619 0.38 1
## enjoyable 13 0.78 0.609 0.39 1
## attractive 3 0.78 0.601 0.40 1
## beautiful 5 0.77 0.587 0.41 1
## elegant 11 0.76 0.572 0.43 1
## pretty 25 0.76 0.571 0.43 1
## lovely 20 0.75 0.560 0.44 1
## delightful 10 0.74 0.553 0.45 1
## inviting 18 0.74 0.541 0.46 1
## satisfying 28 0.73 0.540 0.46 1
## wellDesigned 31 0.71 0.499 0.50 1
## interesting 17 0.70 0.494 0.51 1
## engaging 12 0.70 0.490 0.51 1
## clean 6 0.70 0.484 0.52 1
## harmonious 16 0.69 0.477 0.52 1
## professional 26 0.67 0.450 0.55 1
## exciting 14 0.66 0.440 0.56 1
## motivating 21 0.65 0.424 0.58 1
## tasteful 30 0.64 0.414 0.59 1
## fascinating 15 0.64 0.413 0.59 1
## balanced 4 0.63 0.394 0.61 1
## sophisticated 29 0.63 0.391 0.61 1
## organized 23 0.61 0.378 0.62 1
## colorHarmonious 8 0.59 0.349 0.65 1
## artistic 2 0.49 0.241 0.76 1
## creative 9 0.49 0.240 0.76 1
## cluttered 7 -0.33 0.108 0.89 1
## provoking 27 0.20 0.039 0.96 1
##
## PA1
## SS loadings 14.42
## Proportion Var 0.47
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 434 and the objective function was 6.68
##
## The root mean square of the residuals (RMSR) is 0.09
## The df corrected root mean square of the residuals is 0.09
##
## Fit based upon off diagonal values = 0.97
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.98
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.94
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.79 0.05 0.63 0.37 1.0
## clean 6 0.77 0.19 0.63 0.37 1.1
## professional 26 0.75 0.17 0.60 0.40 1.1
## nice 22 0.75 0.37 0.70 0.30 1.5
## balanced 4 0.73 0.14 0.55 0.45 1.1
## likable 19 0.72 0.38 0.66 0.34 1.5
## wellDesigned 31 0.68 0.30 0.55 0.45 1.4
## harmonious 16 0.68 0.28 0.54 0.46 1.3
## colorHarmonious 8 0.67 0.14 0.47 0.53 1.1
## pleasing 24 0.67 0.46 0.65 0.35 1.8
## appealing 1 0.61 0.52 0.64 0.36 1.9
## satisfying 28 0.61 0.42 0.55 0.45 1.8
## enjoyable 13 0.58 0.51 0.61 0.39 2.0
## tasteful 30 0.58 0.32 0.43 0.57 1.6
## attractive 3 0.57 0.52 0.60 0.40 2.0
## cluttered 7 -0.46 0.02 0.21 0.79 1.0
## exciting 14 0.20 0.79 0.66 0.34 1.1
## fascinating 15 0.21 0.74 0.59 0.41 1.2
## motivating 21 0.27 0.69 0.54 0.46 1.3
## artistic 2 0.06 0.68 0.47 0.53 1.0
## creative 9 0.07 0.67 0.45 0.55 1.0
## delightful 10 0.41 0.66 0.61 0.39 1.7
## inviting 18 0.41 0.65 0.59 0.41 1.7
## beautiful 5 0.46 0.64 0.61 0.39 1.8
## sophisticated 29 0.30 0.60 0.45 0.55 1.5
## engaging 12 0.40 0.60 0.52 0.48 1.8
## lovely 20 0.47 0.59 0.58 0.42 1.9
## elegant 11 0.51 0.56 0.58 0.42 2.0
## pretty 25 0.53 0.54 0.57 0.43 2.0
## interesting 17 0.48 0.52 0.50 0.50 2.0
## provoking 27 -0.06 0.37 0.14 0.86 1.1
##
## PA1 PA2
## SS loadings 9.14 7.73
## Proportion Var 0.29 0.25
## Cumulative Var 0.29 0.54
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.95
## Multiple R square of scores with factors 0.92 0.90
## Minimum correlation of possible factor scores 0.84 0.80
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.94 -0.28 0.63 0.37 1.2
## clean 6 0.86 -0.10 0.63 0.37 1.0
## professional 26 0.84 -0.12 0.60 0.40 1.0
## balanced 4 0.82 -0.15 0.55 0.45 1.1
## colorHarmonious 8 0.76 -0.12 0.47 0.53 1.1
## nice 22 0.75 0.13 0.70 0.30 1.1
## likable 19 0.70 0.15 0.66 0.34 1.1
## harmonious 16 0.70 0.05 0.54 0.46 1.0
## wellDesigned 31 0.69 0.08 0.55 0.45 1.0
## pleasing 24 0.61 0.27 0.65 0.35 1.4
## tasteful 30 0.56 0.14 0.43 0.57 1.1
## cluttered 7 -0.56 0.22 0.21 0.79 1.3
## satisfying 28 0.56 0.25 0.55 0.45 1.4
## appealing 1 0.52 0.37 0.64 0.36 1.8
## enjoyable 13 0.49 0.37 0.61 0.39 1.9
## attractive 3 0.47 0.38 0.60 0.40 1.9
## exciting 14 -0.10 0.87 0.66 0.34 1.0
## fascinating 15 -0.06 0.81 0.59 0.41 1.0
## artistic 2 -0.22 0.80 0.47 0.53 1.2
## creative 9 -0.20 0.78 0.45 0.55 1.1
## motivating 21 0.03 0.72 0.54 0.46 1.0
## delightful 10 0.20 0.63 0.61 0.39 1.2
## inviting 18 0.22 0.61 0.59 0.41 1.3
## sophisticated 29 0.11 0.60 0.45 0.55 1.1
## beautiful 5 0.28 0.57 0.61 0.39 1.5
## engaging 12 0.23 0.55 0.52 0.48 1.3
## lovely 20 0.32 0.52 0.58 0.42 1.7
## provoking 27 -0.23 0.47 0.14 0.86 1.5
## elegant 11 0.38 0.46 0.58 0.42 1.9
## interesting 17 0.36 0.42 0.50 0.50 1.9
## pretty 25 0.42 0.42 0.57 0.43 2.0
##
## PA1 PA2
## SS loadings 9.32 7.54
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.63
## PA2 0.63 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.81 0.653 0.35 1
## pleasing 24 0.80 0.646 0.35 1
## appealing 1 0.80 0.644 0.36 1
## likable 19 0.79 0.619 0.38 1
## enjoyable 13 0.78 0.609 0.39 1
## attractive 3 0.78 0.601 0.40 1
## beautiful 5 0.77 0.587 0.41 1
## elegant 11 0.76 0.572 0.43 1
## pretty 25 0.76 0.571 0.43 1
## lovely 20 0.75 0.560 0.44 1
## delightful 10 0.74 0.553 0.45 1
## inviting 18 0.74 0.541 0.46 1
## satisfying 28 0.73 0.540 0.46 1
## wellDesigned 31 0.71 0.499 0.50 1
## interesting 17 0.70 0.494 0.51 1
## engaging 12 0.70 0.490 0.51 1
## clean 6 0.70 0.484 0.52 1
## harmonious 16 0.69 0.477 0.52 1
## professional 26 0.67 0.450 0.55 1
## exciting 14 0.66 0.440 0.56 1
## motivating 21 0.65 0.424 0.58 1
## tasteful 30 0.64 0.414 0.59 1
## fascinating 15 0.64 0.413 0.59 1
## balanced 4 0.63 0.394 0.61 1
## sophisticated 29 0.63 0.391 0.61 1
## organized 23 0.61 0.378 0.62 1
## colorHarmonious 8 0.59 0.349 0.65 1
## artistic 2 0.49 0.241 0.76 1
## creative 9 0.49 0.240 0.76 1
## cluttered 7 -0.33 0.108 0.89 1
## provoking 27 0.20 0.039 0.96 1
##
## PA1
## SS loadings 14.42
## Proportion Var 0.47
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 434 and the objective function was 6.68
##
## The root mean square of the residuals (RMSR) is 0.09
## The df corrected root mean square of the residuals is 0.09
##
## Fit based upon off diagonal values = 0.97
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.98
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.94
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.79 0.05 0.63 0.37 1.0
## clean 6 0.77 0.19 0.63 0.37 1.1
## professional 26 0.75 0.17 0.60 0.40 1.1
## nice 22 0.75 0.37 0.70 0.30 1.5
## balanced 4 0.73 0.14 0.55 0.45 1.1
## likable 19 0.72 0.38 0.66 0.34 1.5
## wellDesigned 31 0.68 0.30 0.55 0.45 1.4
## harmonious 16 0.68 0.28 0.54 0.46 1.3
## colorHarmonious 8 0.67 0.14 0.47 0.53 1.1
## pleasing 24 0.67 0.46 0.65 0.35 1.8
## appealing 1 0.61 0.52 0.64 0.36 1.9
## satisfying 28 0.61 0.42 0.55 0.45 1.8
## enjoyable 13 0.58 0.51 0.61 0.39 2.0
## tasteful 30 0.58 0.32 0.43 0.57 1.6
## attractive 3 0.57 0.52 0.60 0.40 2.0
## cluttered 7 -0.46 0.02 0.21 0.79 1.0
## exciting 14 0.20 0.79 0.66 0.34 1.1
## fascinating 15 0.21 0.74 0.59 0.41 1.2
## motivating 21 0.27 0.69 0.54 0.46 1.3
## artistic 2 0.06 0.68 0.47 0.53 1.0
## creative 9 0.07 0.67 0.45 0.55 1.0
## delightful 10 0.41 0.66 0.61 0.39 1.7
## inviting 18 0.41 0.65 0.59 0.41 1.7
## beautiful 5 0.46 0.64 0.61 0.39 1.8
## sophisticated 29 0.30 0.60 0.45 0.55 1.5
## engaging 12 0.40 0.60 0.52 0.48 1.8
## lovely 20 0.47 0.59 0.58 0.42 1.9
## elegant 11 0.51 0.56 0.58 0.42 2.0
## pretty 25 0.53 0.54 0.57 0.43 2.0
## interesting 17 0.48 0.52 0.50 0.50 2.0
## provoking 27 -0.06 0.37 0.14 0.86 1.1
##
## PA1 PA2
## SS loadings 9.14 7.73
## Proportion Var 0.29 0.25
## Cumulative Var 0.29 0.54
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.95
## Multiple R square of scores with factors 0.92 0.90
## Minimum correlation of possible factor scores 0.84 0.80
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.94 -0.28 0.63 0.37 1.2
## clean 6 0.86 -0.10 0.63 0.37 1.0
## professional 26 0.84 -0.12 0.60 0.40 1.0
## balanced 4 0.82 -0.15 0.55 0.45 1.1
## colorHarmonious 8 0.76 -0.12 0.47 0.53 1.1
## nice 22 0.75 0.13 0.70 0.30 1.1
## likable 19 0.70 0.15 0.66 0.34 1.1
## harmonious 16 0.70 0.05 0.54 0.46 1.0
## wellDesigned 31 0.69 0.08 0.55 0.45 1.0
## pleasing 24 0.61 0.27 0.65 0.35 1.4
## tasteful 30 0.56 0.14 0.43 0.57 1.1
## cluttered 7 -0.56 0.22 0.21 0.79 1.3
## satisfying 28 0.56 0.25 0.55 0.45 1.4
## appealing 1 0.52 0.37 0.64 0.36 1.8
## enjoyable 13 0.49 0.37 0.61 0.39 1.9
## attractive 3 0.47 0.38 0.60 0.40 1.9
## exciting 14 -0.10 0.87 0.66 0.34 1.0
## fascinating 15 -0.06 0.81 0.59 0.41 1.0
## artistic 2 -0.22 0.80 0.47 0.53 1.2
## creative 9 -0.20 0.78 0.45 0.55 1.1
## motivating 21 0.03 0.72 0.54 0.46 1.0
## delightful 10 0.20 0.63 0.61 0.39 1.2
## inviting 18 0.22 0.61 0.59 0.41 1.3
## sophisticated 29 0.11 0.60 0.45 0.55 1.1
## beautiful 5 0.28 0.57 0.61 0.39 1.5
## engaging 12 0.23 0.55 0.52 0.48 1.3
## lovely 20 0.32 0.52 0.58 0.42 1.7
## provoking 27 -0.23 0.47 0.14 0.86 1.5
## elegant 11 0.38 0.46 0.58 0.42 1.9
## interesting 17 0.36 0.42 0.50 0.50 1.9
## pretty 25 0.42 0.42 0.57 0.43 2.0
##
## PA1 PA2
## SS loadings 9.32 7.54
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.63
## PA2 0.63 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.81 0.653 0.35 1
## pleasing 24 0.80 0.646 0.35 1
## appealing 1 0.80 0.644 0.36 1
## likable 19 0.79 0.619 0.38 1
## enjoyable 13 0.78 0.609 0.39 1
## attractive 3 0.78 0.601 0.40 1
## beautiful 5 0.77 0.587 0.41 1
## elegant 11 0.76 0.572 0.43 1
## pretty 25 0.76 0.571 0.43 1
## lovely 20 0.75 0.560 0.44 1
## delightful 10 0.74 0.553 0.45 1
## inviting 18 0.74 0.541 0.46 1
## satisfying 28 0.73 0.540 0.46 1
## wellDesigned 31 0.71 0.499 0.50 1
## interesting 17 0.70 0.494 0.51 1
## engaging 12 0.70 0.490 0.51 1
## clean 6 0.70 0.484 0.52 1
## harmonious 16 0.69 0.477 0.52 1
## professional 26 0.67 0.450 0.55 1
## exciting 14 0.66 0.440 0.56 1
## motivating 21 0.65 0.424 0.58 1
## tasteful 30 0.64 0.414 0.59 1
## fascinating 15 0.64 0.413 0.59 1
## balanced 4 0.63 0.394 0.61 1
## sophisticated 29 0.63 0.391 0.61 1
## organized 23 0.61 0.378 0.62 1
## colorHarmonious 8 0.59 0.349 0.65 1
## artistic 2 0.49 0.241 0.76 1
## creative 9 0.49 0.240 0.76 1
## cluttered 7 -0.33 0.108 0.89 1
## provoking 27 0.20 0.039 0.96 1
##
## PA1
## SS loadings 14.42
## Proportion Var 0.47
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 434 and the objective function was 6.68
##
## The root mean square of the residuals (RMSR) is 0.09
## The df corrected root mean square of the residuals is 0.09
##
## Fit based upon off diagonal values = 0.97
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.98
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.94
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.79 0.05 0.63 0.37 1.0
## clean 6 0.77 0.19 0.63 0.37 1.1
## professional 26 0.75 0.17 0.60 0.40 1.1
## nice 22 0.75 0.37 0.70 0.30 1.5
## balanced 4 0.73 0.14 0.55 0.45 1.1
## likable 19 0.72 0.38 0.66 0.34 1.5
## wellDesigned 31 0.68 0.30 0.55 0.45 1.4
## harmonious 16 0.68 0.28 0.54 0.46 1.3
## colorHarmonious 8 0.67 0.14 0.47 0.53 1.1
## pleasing 24 0.67 0.46 0.65 0.35 1.8
## appealing 1 0.61 0.52 0.64 0.36 1.9
## satisfying 28 0.61 0.42 0.55 0.45 1.8
## enjoyable 13 0.58 0.51 0.61 0.39 2.0
## tasteful 30 0.58 0.32 0.43 0.57 1.6
## attractive 3 0.57 0.52 0.60 0.40 2.0
## cluttered 7 -0.46 0.02 0.21 0.79 1.0
## exciting 14 0.20 0.79 0.66 0.34 1.1
## fascinating 15 0.21 0.74 0.59 0.41 1.2
## motivating 21 0.27 0.69 0.54 0.46 1.3
## artistic 2 0.06 0.68 0.47 0.53 1.0
## creative 9 0.07 0.67 0.45 0.55 1.0
## delightful 10 0.41 0.66 0.61 0.39 1.7
## inviting 18 0.41 0.65 0.59 0.41 1.7
## beautiful 5 0.46 0.64 0.61 0.39 1.8
## sophisticated 29 0.30 0.60 0.45 0.55 1.5
## engaging 12 0.40 0.60 0.52 0.48 1.8
## lovely 20 0.47 0.59 0.58 0.42 1.9
## elegant 11 0.51 0.56 0.58 0.42 2.0
## pretty 25 0.53 0.54 0.57 0.43 2.0
## interesting 17 0.48 0.52 0.50 0.50 2.0
## provoking 27 -0.06 0.37 0.14 0.86 1.1
##
## PA1 PA2
## SS loadings 9.14 7.73
## Proportion Var 0.29 0.25
## Cumulative Var 0.29 0.54
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.95
## Multiple R square of scores with factors 0.92 0.90
## Minimum correlation of possible factor scores 0.84 0.80
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.94 -0.28 0.63 0.37 1.2
## clean 6 0.86 -0.10 0.63 0.37 1.0
## professional 26 0.84 -0.12 0.60 0.40 1.0
## balanced 4 0.82 -0.15 0.55 0.45 1.1
## colorHarmonious 8 0.76 -0.12 0.47 0.53 1.1
## nice 22 0.75 0.13 0.70 0.30 1.1
## likable 19 0.70 0.15 0.66 0.34 1.1
## harmonious 16 0.70 0.05 0.54 0.46 1.0
## wellDesigned 31 0.69 0.08 0.55 0.45 1.0
## pleasing 24 0.61 0.27 0.65 0.35 1.4
## tasteful 30 0.56 0.14 0.43 0.57 1.1
## cluttered 7 -0.56 0.22 0.21 0.79 1.3
## satisfying 28 0.56 0.25 0.55 0.45 1.4
## appealing 1 0.52 0.37 0.64 0.36 1.8
## enjoyable 13 0.49 0.37 0.61 0.39 1.9
## attractive 3 0.47 0.38 0.60 0.40 1.9
## exciting 14 -0.10 0.87 0.66 0.34 1.0
## fascinating 15 -0.06 0.81 0.59 0.41 1.0
## artistic 2 -0.22 0.80 0.47 0.53 1.2
## creative 9 -0.20 0.78 0.45 0.55 1.1
## motivating 21 0.03 0.72 0.54 0.46 1.0
## delightful 10 0.20 0.63 0.61 0.39 1.2
## inviting 18 0.22 0.61 0.59 0.41 1.3
## sophisticated 29 0.11 0.60 0.45 0.55 1.1
## beautiful 5 0.28 0.57 0.61 0.39 1.5
## engaging 12 0.23 0.55 0.52 0.48 1.3
## lovely 20 0.32 0.52 0.58 0.42 1.7
## provoking 27 -0.23 0.47 0.14 0.86 1.5
## elegant 11 0.38 0.46 0.58 0.42 1.9
## interesting 17 0.36 0.42 0.50 0.50 1.9
## pretty 25 0.42 0.42 0.57 0.43 2.0
##
## PA1 PA2
## SS loadings 9.32 7.54
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.63
## PA2 0.63 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.81 0.653 0.35 1
## pleasing 24 0.80 0.646 0.35 1
## appealing 1 0.80 0.644 0.36 1
## likable 19 0.79 0.619 0.38 1
## enjoyable 13 0.78 0.609 0.39 1
## attractive 3 0.78 0.601 0.40 1
## beautiful 5 0.77 0.587 0.41 1
## elegant 11 0.76 0.572 0.43 1
## pretty 25 0.76 0.571 0.43 1
## lovely 20 0.75 0.560 0.44 1
## delightful 10 0.74 0.553 0.45 1
## inviting 18 0.74 0.541 0.46 1
## satisfying 28 0.73 0.540 0.46 1
## wellDesigned 31 0.71 0.499 0.50 1
## interesting 17 0.70 0.494 0.51 1
## engaging 12 0.70 0.490 0.51 1
## clean 6 0.70 0.484 0.52 1
## harmonious 16 0.69 0.477 0.52 1
## professional 26 0.67 0.450 0.55 1
## exciting 14 0.66 0.440 0.56 1
## motivating 21 0.65 0.424 0.58 1
## tasteful 30 0.64 0.414 0.59 1
## fascinating 15 0.64 0.413 0.59 1
## balanced 4 0.63 0.394 0.61 1
## sophisticated 29 0.63 0.391 0.61 1
## organized 23 0.61 0.378 0.62 1
## colorHarmonious 8 0.59 0.349 0.65 1
## artistic 2 0.49 0.241 0.76 1
## creative 9 0.49 0.240 0.76 1
## cluttered 7 -0.33 0.108 0.89 1
## provoking 27 0.20 0.039 0.96 1
##
## PA1
## SS loadings 14.42
## Proportion Var 0.47
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 434 and the objective function was 6.68
##
## The root mean square of the residuals (RMSR) is 0.09
## The df corrected root mean square of the residuals is 0.09
##
## Fit based upon off diagonal values = 0.97
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.98
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.94
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.79 0.05 0.63 0.37 1.0
## clean 6 0.77 0.19 0.63 0.37 1.1
## professional 26 0.75 0.17 0.60 0.40 1.1
## nice 22 0.75 0.37 0.70 0.30 1.5
## balanced 4 0.73 0.14 0.55 0.45 1.1
## likable 19 0.72 0.38 0.66 0.34 1.5
## wellDesigned 31 0.68 0.30 0.55 0.45 1.4
## harmonious 16 0.68 0.28 0.54 0.46 1.3
## colorHarmonious 8 0.67 0.14 0.47 0.53 1.1
## pleasing 24 0.67 0.46 0.65 0.35 1.8
## appealing 1 0.61 0.52 0.64 0.36 1.9
## satisfying 28 0.61 0.42 0.55 0.45 1.8
## enjoyable 13 0.58 0.51 0.61 0.39 2.0
## tasteful 30 0.58 0.32 0.43 0.57 1.6
## attractive 3 0.57 0.52 0.60 0.40 2.0
## cluttered 7 -0.46 0.02 0.21 0.79 1.0
## exciting 14 0.20 0.79 0.66 0.34 1.1
## fascinating 15 0.21 0.74 0.59 0.41 1.2
## motivating 21 0.27 0.69 0.54 0.46 1.3
## artistic 2 0.06 0.68 0.47 0.53 1.0
## creative 9 0.07 0.67 0.45 0.55 1.0
## delightful 10 0.41 0.66 0.61 0.39 1.7
## inviting 18 0.41 0.65 0.59 0.41 1.7
## beautiful 5 0.46 0.64 0.61 0.39 1.8
## sophisticated 29 0.30 0.60 0.45 0.55 1.5
## engaging 12 0.40 0.60 0.52 0.48 1.8
## lovely 20 0.47 0.59 0.58 0.42 1.9
## elegant 11 0.51 0.56 0.58 0.42 2.0
## pretty 25 0.53 0.54 0.57 0.43 2.0
## interesting 17 0.48 0.52 0.50 0.50 2.0
## provoking 27 -0.06 0.37 0.14 0.86 1.1
##
## PA1 PA2
## SS loadings 9.14 7.73
## Proportion Var 0.29 0.25
## Cumulative Var 0.29 0.54
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.95
## Multiple R square of scores with factors 0.92 0.90
## Minimum correlation of possible factor scores 0.84 0.80
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.94 -0.28 0.63 0.37 1.2
## clean 6 0.86 -0.10 0.63 0.37 1.0
## professional 26 0.84 -0.12 0.60 0.40 1.0
## balanced 4 0.82 -0.15 0.55 0.45 1.1
## colorHarmonious 8 0.76 -0.12 0.47 0.53 1.1
## nice 22 0.75 0.13 0.70 0.30 1.1
## likable 19 0.70 0.15 0.66 0.34 1.1
## harmonious 16 0.70 0.05 0.54 0.46 1.0
## wellDesigned 31 0.69 0.08 0.55 0.45 1.0
## pleasing 24 0.61 0.27 0.65 0.35 1.4
## tasteful 30 0.56 0.14 0.43 0.57 1.1
## cluttered 7 -0.56 0.22 0.21 0.79 1.3
## satisfying 28 0.56 0.25 0.55 0.45 1.4
## appealing 1 0.52 0.37 0.64 0.36 1.8
## enjoyable 13 0.49 0.37 0.61 0.39 1.9
## attractive 3 0.47 0.38 0.60 0.40 1.9
## exciting 14 -0.10 0.87 0.66 0.34 1.0
## fascinating 15 -0.06 0.81 0.59 0.41 1.0
## artistic 2 -0.22 0.80 0.47 0.53 1.2
## creative 9 -0.20 0.78 0.45 0.55 1.1
## motivating 21 0.03 0.72 0.54 0.46 1.0
## delightful 10 0.20 0.63 0.61 0.39 1.2
## inviting 18 0.22 0.61 0.59 0.41 1.3
## sophisticated 29 0.11 0.60 0.45 0.55 1.1
## beautiful 5 0.28 0.57 0.61 0.39 1.5
## engaging 12 0.23 0.55 0.52 0.48 1.3
## lovely 20 0.32 0.52 0.58 0.42 1.7
## provoking 27 -0.23 0.47 0.14 0.86 1.5
## elegant 11 0.38 0.46 0.58 0.42 1.9
## interesting 17 0.36 0.42 0.50 0.50 1.9
## pretty 25 0.42 0.42 0.57 0.43 2.0
##
## PA1 PA2
## SS loadings 9.32 7.54
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.63
## PA2 0.63 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 23.71
## The degrees of freedom for the model are 404 and the objective function was 3.95
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Image 3
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.770 0.23 1
## pleasing 24 0.84 0.699 0.30 1
## enjoyable 13 0.83 0.695 0.30 1
## attractive 3 0.81 0.658 0.34 1
## nice 22 0.81 0.651 0.35 1
## appealing 1 0.80 0.637 0.36 1
## lovely 20 0.78 0.602 0.40 1
## delightful 10 0.78 0.601 0.40 1
## pretty 25 0.77 0.599 0.40 1
## satisfying 28 0.77 0.590 0.41 1
## engaging 12 0.76 0.579 0.42 1
## harmonious 16 0.76 0.578 0.42 1
## beautiful 5 0.76 0.576 0.42 1
## fascinating 15 0.73 0.538 0.46 1
## exciting 14 0.72 0.526 0.47 1
## motivating 21 0.71 0.511 0.49 1
## inviting 18 0.71 0.509 0.49 1
## clean 6 0.71 0.507 0.49 1
## interesting 17 0.71 0.502 0.50 1
## elegant 11 0.71 0.500 0.50 1
## tasteful 30 0.68 0.466 0.53 1
## wellDesigned 31 0.67 0.446 0.55 1
## colorHarmonious 8 0.63 0.400 0.60 1
## sophisticated 29 0.62 0.387 0.61 1
## organized 23 0.62 0.384 0.62 1
## balanced 4 0.61 0.376 0.62 1
## creative 9 0.55 0.306 0.69 1
## professional 26 0.52 0.268 0.73 1
## artistic 2 0.51 0.259 0.74 1
## provoking 27 0.22 0.047 0.95 1
## cluttered 7 0.03 0.001 1.00 1
##
## PA1
## SS loadings 15.17
## Proportion Var 0.49
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 434 and the objective function was 5.55
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.75 0.32 0.6694 0.33 1.4
## beautiful 5 0.75 0.31 0.6512 0.35 1.3
## attractive 3 0.74 0.39 0.6971 0.30 1.5
## delightful 10 0.69 0.39 0.6292 0.37 1.6
## lovely 20 0.69 0.39 0.6290 0.37 1.6
## interesting 17 0.68 0.30 0.5550 0.44 1.4
## creative 9 0.67 0.09 0.4522 0.55 1.0
## fascinating 15 0.66 0.36 0.5662 0.43 1.6
## likable 19 0.65 0.58 0.7674 0.23 2.0
## pleasing 24 0.63 0.55 0.6968 0.30 2.0
## appealing 1 0.62 0.51 0.6363 0.36 1.9
## enjoyable 13 0.62 0.56 0.6933 0.31 2.0
## tasteful 30 0.60 0.35 0.4861 0.51 1.6
## exciting 14 0.60 0.41 0.5328 0.47 1.8
## satisfying 28 0.59 0.49 0.5892 0.41 1.9
## elegant 11 0.57 0.42 0.5033 0.50 1.8
## colorHarmonious 8 0.55 0.33 0.4131 0.59 1.7
## artistic 2 0.54 0.16 0.3172 0.68 1.2
## provoking 27 0.18 0.12 0.0479 0.95 1.8
## cluttered 7 0.04 0.00 0.0019 1.00 1.0
## organized 23 0.13 0.80 0.6616 0.34 1.1
## wellDesigned 31 0.24 0.74 0.6107 0.39 1.2
## balanced 4 0.18 0.73 0.5637 0.44 1.1
## clean 6 0.34 0.70 0.6012 0.40 1.4
## professional 26 0.11 0.66 0.4478 0.55 1.1
## inviting 18 0.40 0.62 0.5481 0.45 1.7
## engaging 12 0.47 0.62 0.6010 0.40 1.9
## harmonious 16 0.50 0.58 0.5891 0.41 2.0
## nice 22 0.57 0.57 0.6518 0.35 2.0
## motivating 21 0.48 0.54 0.5179 0.48 2.0
## sophisticated 29 0.42 0.46 0.3899 0.61 2.0
##
## PA1 PA2
## SS loadings 9.17 7.55
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.93
## Multiple R square of scores with factors 0.89 0.87
## Minimum correlation of possible factor scores 0.78 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.83 -0.26 0.4522 0.55 1.2
## beautiful 5 0.82 -0.02 0.6512 0.35 1.0
## pretty 25 0.82 0.00 0.6694 0.33 1.0
## attractive 3 0.76 0.10 0.6971 0.30 1.0
## interesting 17 0.73 0.02 0.5550 0.44 1.0
## delightful 10 0.70 0.12 0.6292 0.37 1.1
## lovely 20 0.70 0.13 0.6290 0.37 1.1
## fascinating 15 0.67 0.11 0.5662 0.43 1.0
## artistic 2 0.63 -0.09 0.3172 0.68 1.0
## tasteful 30 0.61 0.12 0.4861 0.51 1.1
## exciting 14 0.57 0.20 0.5328 0.47 1.3
## colorHarmonious 8 0.54 0.13 0.4131 0.59 1.1
## likable 19 0.54 0.40 0.7674 0.23 1.8
## appealing 1 0.53 0.32 0.6363 0.36 1.6
## pleasing 24 0.53 0.37 0.6968 0.30 1.8
## elegant 11 0.53 0.23 0.5033 0.50 1.4
## satisfying 28 0.51 0.32 0.5892 0.41 1.7
## enjoyable 13 0.50 0.39 0.6933 0.31 1.9
## provoking 27 0.17 0.06 0.0479 0.95 1.2
## cluttered 7 0.06 -0.03 0.0019 1.00 1.4
## organized 23 -0.27 0.99 0.6616 0.34 1.2
## balanced 4 -0.16 0.86 0.5637 0.44 1.1
## wellDesigned 31 -0.09 0.84 0.6107 0.39 1.0
## professional 26 -0.22 0.81 0.4478 0.55 1.1
## clean 6 0.06 0.73 0.6012 0.40 1.0
## inviting 18 0.19 0.59 0.5481 0.45 1.2
## engaging 12 0.28 0.55 0.6010 0.40 1.5
## harmonious 16 0.33 0.49 0.5891 0.41 1.8
## motivating 21 0.33 0.44 0.5179 0.48 1.8
## nice 22 0.43 0.44 0.6518 0.35 2.0
## sophisticated 29 0.31 0.37 0.3899 0.61 1.9
##
## PA1 PA2
## SS loadings 9.60 7.12
## Proportion Var 0.31 0.23
## Cumulative Var 0.31 0.54
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.770 0.23 1
## pleasing 24 0.84 0.699 0.30 1
## enjoyable 13 0.83 0.695 0.30 1
## attractive 3 0.81 0.658 0.34 1
## nice 22 0.81 0.651 0.35 1
## appealing 1 0.80 0.637 0.36 1
## lovely 20 0.78 0.602 0.40 1
## delightful 10 0.78 0.601 0.40 1
## pretty 25 0.77 0.599 0.40 1
## satisfying 28 0.77 0.590 0.41 1
## engaging 12 0.76 0.579 0.42 1
## harmonious 16 0.76 0.578 0.42 1
## beautiful 5 0.76 0.576 0.42 1
## fascinating 15 0.73 0.538 0.46 1
## exciting 14 0.72 0.526 0.47 1
## motivating 21 0.71 0.511 0.49 1
## inviting 18 0.71 0.509 0.49 1
## clean 6 0.71 0.507 0.49 1
## interesting 17 0.71 0.502 0.50 1
## elegant 11 0.71 0.500 0.50 1
## tasteful 30 0.68 0.466 0.53 1
## wellDesigned 31 0.67 0.446 0.55 1
## colorHarmonious 8 0.63 0.400 0.60 1
## sophisticated 29 0.62 0.387 0.61 1
## organized 23 0.62 0.384 0.62 1
## balanced 4 0.61 0.376 0.62 1
## creative 9 0.55 0.306 0.69 1
## professional 26 0.52 0.268 0.73 1
## artistic 2 0.51 0.259 0.74 1
## provoking 27 0.22 0.047 0.95 1
## cluttered 7 0.03 0.001 1.00 1
##
## PA1
## SS loadings 15.17
## Proportion Var 0.49
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 434 and the objective function was 5.55
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.75 0.32 0.6694 0.33 1.4
## beautiful 5 0.75 0.31 0.6512 0.35 1.3
## attractive 3 0.74 0.39 0.6971 0.30 1.5
## delightful 10 0.69 0.39 0.6292 0.37 1.6
## lovely 20 0.69 0.39 0.6290 0.37 1.6
## interesting 17 0.68 0.30 0.5550 0.44 1.4
## creative 9 0.67 0.09 0.4522 0.55 1.0
## fascinating 15 0.66 0.36 0.5662 0.43 1.6
## likable 19 0.65 0.58 0.7674 0.23 2.0
## pleasing 24 0.63 0.55 0.6968 0.30 2.0
## appealing 1 0.62 0.51 0.6363 0.36 1.9
## enjoyable 13 0.62 0.56 0.6933 0.31 2.0
## tasteful 30 0.60 0.35 0.4861 0.51 1.6
## exciting 14 0.60 0.41 0.5328 0.47 1.8
## satisfying 28 0.59 0.49 0.5892 0.41 1.9
## elegant 11 0.57 0.42 0.5033 0.50 1.8
## colorHarmonious 8 0.55 0.33 0.4131 0.59 1.7
## artistic 2 0.54 0.16 0.3172 0.68 1.2
## provoking 27 0.18 0.12 0.0479 0.95 1.8
## cluttered 7 0.04 0.00 0.0019 1.00 1.0
## organized 23 0.13 0.80 0.6616 0.34 1.1
## wellDesigned 31 0.24 0.74 0.6107 0.39 1.2
## balanced 4 0.18 0.73 0.5637 0.44 1.1
## clean 6 0.34 0.70 0.6012 0.40 1.4
## professional 26 0.11 0.66 0.4478 0.55 1.1
## inviting 18 0.40 0.62 0.5481 0.45 1.7
## engaging 12 0.47 0.62 0.6010 0.40 1.9
## harmonious 16 0.50 0.58 0.5891 0.41 2.0
## nice 22 0.57 0.57 0.6518 0.35 2.0
## motivating 21 0.48 0.54 0.5179 0.48 2.0
## sophisticated 29 0.42 0.46 0.3899 0.61 2.0
##
## PA1 PA2
## SS loadings 9.17 7.55
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.93
## Multiple R square of scores with factors 0.89 0.87
## Minimum correlation of possible factor scores 0.78 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.83 -0.26 0.4522 0.55 1.2
## beautiful 5 0.82 -0.02 0.6512 0.35 1.0
## pretty 25 0.82 0.00 0.6694 0.33 1.0
## attractive 3 0.76 0.10 0.6971 0.30 1.0
## interesting 17 0.73 0.02 0.5550 0.44 1.0
## delightful 10 0.70 0.12 0.6292 0.37 1.1
## lovely 20 0.70 0.13 0.6290 0.37 1.1
## fascinating 15 0.67 0.11 0.5662 0.43 1.0
## artistic 2 0.63 -0.09 0.3172 0.68 1.0
## tasteful 30 0.61 0.12 0.4861 0.51 1.1
## exciting 14 0.57 0.20 0.5328 0.47 1.3
## colorHarmonious 8 0.54 0.13 0.4131 0.59 1.1
## likable 19 0.54 0.40 0.7674 0.23 1.8
## appealing 1 0.53 0.32 0.6363 0.36 1.6
## pleasing 24 0.53 0.37 0.6968 0.30 1.8
## elegant 11 0.53 0.23 0.5033 0.50 1.4
## satisfying 28 0.51 0.32 0.5892 0.41 1.7
## enjoyable 13 0.50 0.39 0.6933 0.31 1.9
## provoking 27 0.17 0.06 0.0479 0.95 1.2
## cluttered 7 0.06 -0.03 0.0019 1.00 1.4
## organized 23 -0.27 0.99 0.6616 0.34 1.2
## balanced 4 -0.16 0.86 0.5637 0.44 1.1
## wellDesigned 31 -0.09 0.84 0.6107 0.39 1.0
## professional 26 -0.22 0.81 0.4478 0.55 1.1
## clean 6 0.06 0.73 0.6012 0.40 1.0
## inviting 18 0.19 0.59 0.5481 0.45 1.2
## engaging 12 0.28 0.55 0.6010 0.40 1.5
## harmonious 16 0.33 0.49 0.5891 0.41 1.8
## motivating 21 0.33 0.44 0.5179 0.48 1.8
## nice 22 0.43 0.44 0.6518 0.35 2.0
## sophisticated 29 0.31 0.37 0.3899 0.61 1.9
##
## PA1 PA2
## SS loadings 9.60 7.12
## Proportion Var 0.31 0.23
## Cumulative Var 0.31 0.54
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.770 0.23 1
## pleasing 24 0.84 0.699 0.30 1
## enjoyable 13 0.83 0.695 0.30 1
## attractive 3 0.81 0.658 0.34 1
## nice 22 0.81 0.651 0.35 1
## appealing 1 0.80 0.637 0.36 1
## lovely 20 0.78 0.602 0.40 1
## delightful 10 0.78 0.601 0.40 1
## pretty 25 0.77 0.599 0.40 1
## satisfying 28 0.77 0.590 0.41 1
## engaging 12 0.76 0.579 0.42 1
## harmonious 16 0.76 0.578 0.42 1
## beautiful 5 0.76 0.576 0.42 1
## fascinating 15 0.73 0.538 0.46 1
## exciting 14 0.72 0.526 0.47 1
## motivating 21 0.71 0.511 0.49 1
## inviting 18 0.71 0.509 0.49 1
## clean 6 0.71 0.507 0.49 1
## interesting 17 0.71 0.502 0.50 1
## elegant 11 0.71 0.500 0.50 1
## tasteful 30 0.68 0.466 0.53 1
## wellDesigned 31 0.67 0.446 0.55 1
## colorHarmonious 8 0.63 0.400 0.60 1
## sophisticated 29 0.62 0.387 0.61 1
## organized 23 0.62 0.384 0.62 1
## balanced 4 0.61 0.376 0.62 1
## creative 9 0.55 0.306 0.69 1
## professional 26 0.52 0.268 0.73 1
## artistic 2 0.51 0.259 0.74 1
## provoking 27 0.22 0.047 0.95 1
## cluttered 7 0.03 0.001 1.00 1
##
## PA1
## SS loadings 15.17
## Proportion Var 0.49
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 434 and the objective function was 5.55
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.75 0.32 0.6694 0.33 1.4
## beautiful 5 0.75 0.31 0.6512 0.35 1.3
## attractive 3 0.74 0.39 0.6971 0.30 1.5
## delightful 10 0.69 0.39 0.6292 0.37 1.6
## lovely 20 0.69 0.39 0.6290 0.37 1.6
## interesting 17 0.68 0.30 0.5550 0.44 1.4
## creative 9 0.67 0.09 0.4522 0.55 1.0
## fascinating 15 0.66 0.36 0.5662 0.43 1.6
## likable 19 0.65 0.58 0.7674 0.23 2.0
## pleasing 24 0.63 0.55 0.6968 0.30 2.0
## appealing 1 0.62 0.51 0.6363 0.36 1.9
## enjoyable 13 0.62 0.56 0.6933 0.31 2.0
## tasteful 30 0.60 0.35 0.4861 0.51 1.6
## exciting 14 0.60 0.41 0.5328 0.47 1.8
## satisfying 28 0.59 0.49 0.5892 0.41 1.9
## elegant 11 0.57 0.42 0.5033 0.50 1.8
## colorHarmonious 8 0.55 0.33 0.4131 0.59 1.7
## artistic 2 0.54 0.16 0.3172 0.68 1.2
## provoking 27 0.18 0.12 0.0479 0.95 1.8
## cluttered 7 0.04 0.00 0.0019 1.00 1.0
## organized 23 0.13 0.80 0.6616 0.34 1.1
## wellDesigned 31 0.24 0.74 0.6107 0.39 1.2
## balanced 4 0.18 0.73 0.5637 0.44 1.1
## clean 6 0.34 0.70 0.6012 0.40 1.4
## professional 26 0.11 0.66 0.4478 0.55 1.1
## inviting 18 0.40 0.62 0.5481 0.45 1.7
## engaging 12 0.47 0.62 0.6010 0.40 1.9
## harmonious 16 0.50 0.58 0.5891 0.41 2.0
## nice 22 0.57 0.57 0.6518 0.35 2.0
## motivating 21 0.48 0.54 0.5179 0.48 2.0
## sophisticated 29 0.42 0.46 0.3899 0.61 2.0
##
## PA1 PA2
## SS loadings 9.17 7.55
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.93
## Multiple R square of scores with factors 0.89 0.87
## Minimum correlation of possible factor scores 0.78 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.83 -0.26 0.4522 0.55 1.2
## beautiful 5 0.82 -0.02 0.6512 0.35 1.0
## pretty 25 0.82 0.00 0.6694 0.33 1.0
## attractive 3 0.76 0.10 0.6971 0.30 1.0
## interesting 17 0.73 0.02 0.5550 0.44 1.0
## delightful 10 0.70 0.12 0.6292 0.37 1.1
## lovely 20 0.70 0.13 0.6290 0.37 1.1
## fascinating 15 0.67 0.11 0.5662 0.43 1.0
## artistic 2 0.63 -0.09 0.3172 0.68 1.0
## tasteful 30 0.61 0.12 0.4861 0.51 1.1
## exciting 14 0.57 0.20 0.5328 0.47 1.3
## colorHarmonious 8 0.54 0.13 0.4131 0.59 1.1
## likable 19 0.54 0.40 0.7674 0.23 1.8
## appealing 1 0.53 0.32 0.6363 0.36 1.6
## pleasing 24 0.53 0.37 0.6968 0.30 1.8
## elegant 11 0.53 0.23 0.5033 0.50 1.4
## satisfying 28 0.51 0.32 0.5892 0.41 1.7
## enjoyable 13 0.50 0.39 0.6933 0.31 1.9
## provoking 27 0.17 0.06 0.0479 0.95 1.2
## cluttered 7 0.06 -0.03 0.0019 1.00 1.4
## organized 23 -0.27 0.99 0.6616 0.34 1.2
## balanced 4 -0.16 0.86 0.5637 0.44 1.1
## wellDesigned 31 -0.09 0.84 0.6107 0.39 1.0
## professional 26 -0.22 0.81 0.4478 0.55 1.1
## clean 6 0.06 0.73 0.6012 0.40 1.0
## inviting 18 0.19 0.59 0.5481 0.45 1.2
## engaging 12 0.28 0.55 0.6010 0.40 1.5
## harmonious 16 0.33 0.49 0.5891 0.41 1.8
## motivating 21 0.33 0.44 0.5179 0.48 1.8
## nice 22 0.43 0.44 0.6518 0.35 2.0
## sophisticated 29 0.31 0.37 0.3899 0.61 1.9
##
## PA1 PA2
## SS loadings 9.60 7.12
## Proportion Var 0.31 0.23
## Cumulative Var 0.31 0.54
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.770 0.23 1
## pleasing 24 0.84 0.699 0.30 1
## enjoyable 13 0.83 0.695 0.30 1
## attractive 3 0.81 0.658 0.34 1
## nice 22 0.81 0.651 0.35 1
## appealing 1 0.80 0.637 0.36 1
## lovely 20 0.78 0.602 0.40 1
## delightful 10 0.78 0.601 0.40 1
## pretty 25 0.77 0.599 0.40 1
## satisfying 28 0.77 0.590 0.41 1
## engaging 12 0.76 0.579 0.42 1
## harmonious 16 0.76 0.578 0.42 1
## beautiful 5 0.76 0.576 0.42 1
## fascinating 15 0.73 0.538 0.46 1
## exciting 14 0.72 0.526 0.47 1
## motivating 21 0.71 0.511 0.49 1
## inviting 18 0.71 0.509 0.49 1
## clean 6 0.71 0.507 0.49 1
## interesting 17 0.71 0.502 0.50 1
## elegant 11 0.71 0.500 0.50 1
## tasteful 30 0.68 0.466 0.53 1
## wellDesigned 31 0.67 0.446 0.55 1
## colorHarmonious 8 0.63 0.400 0.60 1
## sophisticated 29 0.62 0.387 0.61 1
## organized 23 0.62 0.384 0.62 1
## balanced 4 0.61 0.376 0.62 1
## creative 9 0.55 0.306 0.69 1
## professional 26 0.52 0.268 0.73 1
## artistic 2 0.51 0.259 0.74 1
## provoking 27 0.22 0.047 0.95 1
## cluttered 7 0.03 0.001 1.00 1
##
## PA1
## SS loadings 15.17
## Proportion Var 0.49
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 434 and the objective function was 5.55
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.75 0.32 0.6694 0.33 1.4
## beautiful 5 0.75 0.31 0.6512 0.35 1.3
## attractive 3 0.74 0.39 0.6971 0.30 1.5
## delightful 10 0.69 0.39 0.6292 0.37 1.6
## lovely 20 0.69 0.39 0.6290 0.37 1.6
## interesting 17 0.68 0.30 0.5550 0.44 1.4
## creative 9 0.67 0.09 0.4522 0.55 1.0
## fascinating 15 0.66 0.36 0.5662 0.43 1.6
## likable 19 0.65 0.58 0.7674 0.23 2.0
## pleasing 24 0.63 0.55 0.6968 0.30 2.0
## appealing 1 0.62 0.51 0.6363 0.36 1.9
## enjoyable 13 0.62 0.56 0.6933 0.31 2.0
## tasteful 30 0.60 0.35 0.4861 0.51 1.6
## exciting 14 0.60 0.41 0.5328 0.47 1.8
## satisfying 28 0.59 0.49 0.5892 0.41 1.9
## elegant 11 0.57 0.42 0.5033 0.50 1.8
## colorHarmonious 8 0.55 0.33 0.4131 0.59 1.7
## artistic 2 0.54 0.16 0.3172 0.68 1.2
## provoking 27 0.18 0.12 0.0479 0.95 1.8
## cluttered 7 0.04 0.00 0.0019 1.00 1.0
## organized 23 0.13 0.80 0.6616 0.34 1.1
## wellDesigned 31 0.24 0.74 0.6107 0.39 1.2
## balanced 4 0.18 0.73 0.5637 0.44 1.1
## clean 6 0.34 0.70 0.6012 0.40 1.4
## professional 26 0.11 0.66 0.4478 0.55 1.1
## inviting 18 0.40 0.62 0.5481 0.45 1.7
## engaging 12 0.47 0.62 0.6010 0.40 1.9
## harmonious 16 0.50 0.58 0.5891 0.41 2.0
## nice 22 0.57 0.57 0.6518 0.35 2.0
## motivating 21 0.48 0.54 0.5179 0.48 2.0
## sophisticated 29 0.42 0.46 0.3899 0.61 2.0
##
## PA1 PA2
## SS loadings 9.17 7.55
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.93
## Multiple R square of scores with factors 0.89 0.87
## Minimum correlation of possible factor scores 0.78 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.83 -0.26 0.4522 0.55 1.2
## beautiful 5 0.82 -0.02 0.6512 0.35 1.0
## pretty 25 0.82 0.00 0.6694 0.33 1.0
## attractive 3 0.76 0.10 0.6971 0.30 1.0
## interesting 17 0.73 0.02 0.5550 0.44 1.0
## delightful 10 0.70 0.12 0.6292 0.37 1.1
## lovely 20 0.70 0.13 0.6290 0.37 1.1
## fascinating 15 0.67 0.11 0.5662 0.43 1.0
## artistic 2 0.63 -0.09 0.3172 0.68 1.0
## tasteful 30 0.61 0.12 0.4861 0.51 1.1
## exciting 14 0.57 0.20 0.5328 0.47 1.3
## colorHarmonious 8 0.54 0.13 0.4131 0.59 1.1
## likable 19 0.54 0.40 0.7674 0.23 1.8
## appealing 1 0.53 0.32 0.6363 0.36 1.6
## pleasing 24 0.53 0.37 0.6968 0.30 1.8
## elegant 11 0.53 0.23 0.5033 0.50 1.4
## satisfying 28 0.51 0.32 0.5892 0.41 1.7
## enjoyable 13 0.50 0.39 0.6933 0.31 1.9
## provoking 27 0.17 0.06 0.0479 0.95 1.2
## cluttered 7 0.06 -0.03 0.0019 1.00 1.4
## organized 23 -0.27 0.99 0.6616 0.34 1.2
## balanced 4 -0.16 0.86 0.5637 0.44 1.1
## wellDesigned 31 -0.09 0.84 0.6107 0.39 1.0
## professional 26 -0.22 0.81 0.4478 0.55 1.1
## clean 6 0.06 0.73 0.6012 0.40 1.0
## inviting 18 0.19 0.59 0.5481 0.45 1.2
## engaging 12 0.28 0.55 0.6010 0.40 1.5
## harmonious 16 0.33 0.49 0.5891 0.41 1.8
## motivating 21 0.33 0.44 0.5179 0.48 1.8
## nice 22 0.43 0.44 0.6518 0.35 2.0
## sophisticated 29 0.31 0.37 0.3899 0.61 1.9
##
## PA1 PA2
## SS loadings 9.60 7.12
## Proportion Var 0.31 0.23
## Cumulative Var 0.31 0.54
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.770 0.23 1
## pleasing 24 0.84 0.699 0.30 1
## enjoyable 13 0.83 0.695 0.30 1
## attractive 3 0.81 0.658 0.34 1
## nice 22 0.81 0.651 0.35 1
## appealing 1 0.80 0.637 0.36 1
## lovely 20 0.78 0.602 0.40 1
## delightful 10 0.78 0.601 0.40 1
## pretty 25 0.77 0.599 0.40 1
## satisfying 28 0.77 0.590 0.41 1
## engaging 12 0.76 0.579 0.42 1
## harmonious 16 0.76 0.578 0.42 1
## beautiful 5 0.76 0.576 0.42 1
## fascinating 15 0.73 0.538 0.46 1
## exciting 14 0.72 0.526 0.47 1
## motivating 21 0.71 0.511 0.49 1
## inviting 18 0.71 0.509 0.49 1
## clean 6 0.71 0.507 0.49 1
## interesting 17 0.71 0.502 0.50 1
## elegant 11 0.71 0.500 0.50 1
## tasteful 30 0.68 0.466 0.53 1
## wellDesigned 31 0.67 0.446 0.55 1
## colorHarmonious 8 0.63 0.400 0.60 1
## sophisticated 29 0.62 0.387 0.61 1
## organized 23 0.62 0.384 0.62 1
## balanced 4 0.61 0.376 0.62 1
## creative 9 0.55 0.306 0.69 1
## professional 26 0.52 0.268 0.73 1
## artistic 2 0.51 0.259 0.74 1
## provoking 27 0.22 0.047 0.95 1
## cluttered 7 0.03 0.001 1.00 1
##
## PA1
## SS loadings 15.17
## Proportion Var 0.49
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 434 and the objective function was 5.55
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.75 0.32 0.6694 0.33 1.4
## beautiful 5 0.75 0.31 0.6512 0.35 1.3
## attractive 3 0.74 0.39 0.6971 0.30 1.5
## delightful 10 0.69 0.39 0.6292 0.37 1.6
## lovely 20 0.69 0.39 0.6290 0.37 1.6
## interesting 17 0.68 0.30 0.5550 0.44 1.4
## creative 9 0.67 0.09 0.4522 0.55 1.0
## fascinating 15 0.66 0.36 0.5662 0.43 1.6
## likable 19 0.65 0.58 0.7674 0.23 2.0
## pleasing 24 0.63 0.55 0.6968 0.30 2.0
## appealing 1 0.62 0.51 0.6363 0.36 1.9
## enjoyable 13 0.62 0.56 0.6933 0.31 2.0
## tasteful 30 0.60 0.35 0.4861 0.51 1.6
## exciting 14 0.60 0.41 0.5328 0.47 1.8
## satisfying 28 0.59 0.49 0.5892 0.41 1.9
## elegant 11 0.57 0.42 0.5033 0.50 1.8
## colorHarmonious 8 0.55 0.33 0.4131 0.59 1.7
## artistic 2 0.54 0.16 0.3172 0.68 1.2
## provoking 27 0.18 0.12 0.0479 0.95 1.8
## cluttered 7 0.04 0.00 0.0019 1.00 1.0
## organized 23 0.13 0.80 0.6616 0.34 1.1
## wellDesigned 31 0.24 0.74 0.6107 0.39 1.2
## balanced 4 0.18 0.73 0.5637 0.44 1.1
## clean 6 0.34 0.70 0.6012 0.40 1.4
## professional 26 0.11 0.66 0.4478 0.55 1.1
## inviting 18 0.40 0.62 0.5481 0.45 1.7
## engaging 12 0.47 0.62 0.6010 0.40 1.9
## harmonious 16 0.50 0.58 0.5891 0.41 2.0
## nice 22 0.57 0.57 0.6518 0.35 2.0
## motivating 21 0.48 0.54 0.5179 0.48 2.0
## sophisticated 29 0.42 0.46 0.3899 0.61 2.0
##
## PA1 PA2
## SS loadings 9.17 7.55
## Proportion Var 0.30 0.24
## Cumulative Var 0.30 0.54
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.93
## Multiple R square of scores with factors 0.89 0.87
## Minimum correlation of possible factor scores 0.78 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.83 -0.26 0.4522 0.55 1.2
## beautiful 5 0.82 -0.02 0.6512 0.35 1.0
## pretty 25 0.82 0.00 0.6694 0.33 1.0
## attractive 3 0.76 0.10 0.6971 0.30 1.0
## interesting 17 0.73 0.02 0.5550 0.44 1.0
## delightful 10 0.70 0.12 0.6292 0.37 1.1
## lovely 20 0.70 0.13 0.6290 0.37 1.1
## fascinating 15 0.67 0.11 0.5662 0.43 1.0
## artistic 2 0.63 -0.09 0.3172 0.68 1.0
## tasteful 30 0.61 0.12 0.4861 0.51 1.1
## exciting 14 0.57 0.20 0.5328 0.47 1.3
## colorHarmonious 8 0.54 0.13 0.4131 0.59 1.1
## likable 19 0.54 0.40 0.7674 0.23 1.8
## appealing 1 0.53 0.32 0.6363 0.36 1.6
## pleasing 24 0.53 0.37 0.6968 0.30 1.8
## elegant 11 0.53 0.23 0.5033 0.50 1.4
## satisfying 28 0.51 0.32 0.5892 0.41 1.7
## enjoyable 13 0.50 0.39 0.6933 0.31 1.9
## provoking 27 0.17 0.06 0.0479 0.95 1.2
## cluttered 7 0.06 -0.03 0.0019 1.00 1.4
## organized 23 -0.27 0.99 0.6616 0.34 1.2
## balanced 4 -0.16 0.86 0.5637 0.44 1.1
## wellDesigned 31 -0.09 0.84 0.6107 0.39 1.0
## professional 26 -0.22 0.81 0.4478 0.55 1.1
## clean 6 0.06 0.73 0.6012 0.40 1.0
## inviting 18 0.19 0.59 0.5481 0.45 1.2
## engaging 12 0.28 0.55 0.6010 0.40 1.5
## harmonious 16 0.33 0.49 0.5891 0.41 1.8
## motivating 21 0.33 0.44 0.5179 0.48 1.8
## nice 22 0.43 0.44 0.6518 0.35 2.0
## sophisticated 29 0.31 0.37 0.3899 0.61 1.9
##
## PA1 PA2
## SS loadings 9.60 7.12
## Proportion Var 0.31 0.23
## Cumulative Var 0.31 0.54
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 24.45
## The degrees of freedom for the model are 404 and the objective function was 3.98
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.91 0.88
##
##
## ## Image 4
## Warning in readfun(f, ...): libpng warning: iCCP: known incorrect sRGB profile
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.88 0.774 0.23 1
## likable 19 0.87 0.752 0.25 1
## enjoyable 13 0.86 0.741 0.26 1
## delightful 10 0.85 0.716 0.28 1
## appealing 1 0.84 0.711 0.29 1
## satisfying 28 0.83 0.696 0.30 1
## nice 22 0.82 0.677 0.32 1
## lovely 20 0.82 0.670 0.33 1
## attractive 3 0.81 0.658 0.34 1
## beautiful 5 0.79 0.626 0.37 1
## pretty 25 0.78 0.607 0.39 1
## elegant 11 0.78 0.604 0.40 1
## wellDesigned 31 0.77 0.589 0.41 1
## fascinating 15 0.77 0.588 0.41 1
## motivating 21 0.77 0.587 0.41 1
## exciting 14 0.76 0.582 0.42 1
## harmonious 16 0.75 0.559 0.44 1
## engaging 12 0.74 0.553 0.45 1
## interesting 17 0.74 0.544 0.46 1
## organized 23 0.74 0.541 0.46 1
## balanced 4 0.73 0.539 0.46 1
## inviting 18 0.73 0.535 0.47 1
## tasteful 30 0.72 0.518 0.48 1
## clean 6 0.64 0.413 0.59 1
## sophisticated 29 0.63 0.403 0.60 1
## colorHarmonious 8 0.63 0.403 0.60 1
## professional 26 0.61 0.374 0.63 1
## creative 9 0.60 0.362 0.64 1
## artistic 2 0.59 0.347 0.65 1
## provoking 27 0.28 0.081 0.92 1
## cluttered 7 0.15 0.022 0.98 1
##
## PA1
## SS loadings 16.77
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 434 and the objective function was 5.73
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.26 0.692 0.31 1.2
## beautiful 5 0.78 0.29 0.697 0.30 1.3
## attractive 3 0.77 0.33 0.706 0.29 1.4
## appealing 1 0.75 0.41 0.730 0.27 1.6
## fascinating 15 0.74 0.30 0.640 0.36 1.3
## enjoyable 13 0.74 0.45 0.751 0.25 1.7
## pleasing 24 0.73 0.49 0.778 0.22 1.7
## nice 22 0.73 0.40 0.696 0.30 1.6
## likable 19 0.70 0.51 0.752 0.25 1.8
## artistic 2 0.67 0.10 0.465 0.54 1.0
## exciting 14 0.67 0.38 0.595 0.40 1.6
## lovely 20 0.67 0.48 0.670 0.33 1.8
## creative 9 0.65 0.15 0.443 0.56 1.1
## delightful 10 0.64 0.55 0.715 0.29 1.9
## interesting 17 0.64 0.38 0.553 0.45 1.6
## satisfying 28 0.61 0.58 0.701 0.30 2.0
## tasteful 30 0.58 0.43 0.517 0.48 1.8
## colorHarmonious 8 0.53 0.35 0.406 0.59 1.7
## engaging 12 0.53 0.53 0.559 0.44 2.0
## sophisticated 29 0.46 0.44 0.407 0.59 2.0
## provoking 27 0.31 0.06 0.101 0.90 1.1
## organized 23 0.32 0.79 0.732 0.27 1.3
## balanced 4 0.38 0.72 0.654 0.35 1.5
## clean 6 0.27 0.70 0.568 0.43 1.3
## professional 26 0.24 0.69 0.530 0.47 1.2
## harmonious 16 0.45 0.63 0.607 0.39 1.8
## motivating 21 0.50 0.61 0.617 0.38 1.9
## wellDesigned 31 0.51 0.60 0.614 0.39 1.9
## elegant 11 0.53 0.58 0.621 0.38 2.0
## inviting 18 0.52 0.53 0.543 0.46 2.0
## cluttered 7 -0.01 0.26 0.067 0.93 1.0
##
## PA1 PA2
## SS loadings 10.86 7.26
## Proportion Var 0.35 0.23
## Cumulative Var 0.35 0.58
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.92
## Multiple R square of scores with factors 0.90 0.85
## Minimum correlation of possible factor scores 0.80 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.90 -0.10 0.692 0.31 1.0
## beautiful 5 0.88 -0.07 0.697 0.30 1.0
## artistic 2 0.84 -0.25 0.465 0.54 1.2
## attractive 3 0.84 0.00 0.706 0.29 1.0
## fascinating 15 0.82 -0.02 0.640 0.36 1.0
## creative 9 0.78 -0.17 0.443 0.56 1.1
## appealing 1 0.76 0.13 0.730 0.27 1.1
## nice 22 0.75 0.12 0.696 0.30 1.0
## enjoyable 13 0.73 0.18 0.751 0.25 1.1
## pleasing 24 0.70 0.23 0.778 0.22 1.2
## exciting 14 0.68 0.12 0.595 0.40 1.1
## likable 19 0.64 0.28 0.752 0.25 1.4
## interesting 17 0.64 0.14 0.553 0.45 1.1
## lovely 20 0.62 0.25 0.670 0.33 1.3
## delightful 10 0.55 0.36 0.715 0.29 1.7
## tasteful 30 0.52 0.24 0.517 0.48 1.4
## colorHarmonious 8 0.51 0.16 0.406 0.59 1.2
## satisfying 28 0.48 0.42 0.701 0.30 2.0
## engaging 12 0.41 0.40 0.559 0.44 2.0
## provoking 27 0.38 -0.09 0.101 0.90 1.1
## sophisticated 29 0.36 0.33 0.407 0.59 2.0
## organized 23 -0.03 0.88 0.732 0.27 1.0
## clean 6 -0.04 0.79 0.568 0.43 1.0
## professional 26 -0.07 0.78 0.530 0.47 1.0
## balanced 4 0.09 0.74 0.654 0.35 1.0
## harmonious 16 0.24 0.58 0.607 0.39 1.3
## motivating 21 0.31 0.53 0.617 0.38 1.6
## wellDesigned 31 0.33 0.51 0.614 0.39 1.7
## elegant 11 0.37 0.47 0.621 0.38 1.9
## inviting 18 0.39 0.41 0.543 0.46 2.0
## cluttered 7 -0.17 0.35 0.067 0.93 1.4
##
## PA1 PA2
## SS loadings 11.66 6.47
## Proportion Var 0.38 0.21
## Cumulative Var 0.38 0.58
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.93 0.87
## Warning in readfun(f, ...): libpng warning: iCCP: known incorrect sRGB profile
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.88 0.774 0.23 1
## likable 19 0.87 0.752 0.25 1
## enjoyable 13 0.86 0.741 0.26 1
## delightful 10 0.85 0.716 0.28 1
## appealing 1 0.84 0.711 0.29 1
## satisfying 28 0.83 0.696 0.30 1
## nice 22 0.82 0.677 0.32 1
## lovely 20 0.82 0.670 0.33 1
## attractive 3 0.81 0.658 0.34 1
## beautiful 5 0.79 0.626 0.37 1
## pretty 25 0.78 0.607 0.39 1
## elegant 11 0.78 0.604 0.40 1
## wellDesigned 31 0.77 0.589 0.41 1
## fascinating 15 0.77 0.588 0.41 1
## motivating 21 0.77 0.587 0.41 1
## exciting 14 0.76 0.582 0.42 1
## harmonious 16 0.75 0.559 0.44 1
## engaging 12 0.74 0.553 0.45 1
## interesting 17 0.74 0.544 0.46 1
## organized 23 0.74 0.541 0.46 1
## balanced 4 0.73 0.539 0.46 1
## inviting 18 0.73 0.535 0.47 1
## tasteful 30 0.72 0.518 0.48 1
## clean 6 0.64 0.413 0.59 1
## sophisticated 29 0.63 0.403 0.60 1
## colorHarmonious 8 0.63 0.403 0.60 1
## professional 26 0.61 0.374 0.63 1
## creative 9 0.60 0.362 0.64 1
## artistic 2 0.59 0.347 0.65 1
## provoking 27 0.28 0.081 0.92 1
## cluttered 7 0.15 0.022 0.98 1
##
## PA1
## SS loadings 16.77
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 434 and the objective function was 5.73
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.26 0.692 0.31 1.2
## beautiful 5 0.78 0.29 0.697 0.30 1.3
## attractive 3 0.77 0.33 0.706 0.29 1.4
## appealing 1 0.75 0.41 0.730 0.27 1.6
## fascinating 15 0.74 0.30 0.640 0.36 1.3
## enjoyable 13 0.74 0.45 0.751 0.25 1.7
## pleasing 24 0.73 0.49 0.778 0.22 1.7
## nice 22 0.73 0.40 0.696 0.30 1.6
## likable 19 0.70 0.51 0.752 0.25 1.8
## artistic 2 0.67 0.10 0.465 0.54 1.0
## exciting 14 0.67 0.38 0.595 0.40 1.6
## lovely 20 0.67 0.48 0.670 0.33 1.8
## creative 9 0.65 0.15 0.443 0.56 1.1
## delightful 10 0.64 0.55 0.715 0.29 1.9
## interesting 17 0.64 0.38 0.553 0.45 1.6
## satisfying 28 0.61 0.58 0.701 0.30 2.0
## tasteful 30 0.58 0.43 0.517 0.48 1.8
## colorHarmonious 8 0.53 0.35 0.406 0.59 1.7
## engaging 12 0.53 0.53 0.559 0.44 2.0
## sophisticated 29 0.46 0.44 0.407 0.59 2.0
## provoking 27 0.31 0.06 0.101 0.90 1.1
## organized 23 0.32 0.79 0.732 0.27 1.3
## balanced 4 0.38 0.72 0.654 0.35 1.5
## clean 6 0.27 0.70 0.568 0.43 1.3
## professional 26 0.24 0.69 0.530 0.47 1.2
## harmonious 16 0.45 0.63 0.607 0.39 1.8
## motivating 21 0.50 0.61 0.617 0.38 1.9
## wellDesigned 31 0.51 0.60 0.614 0.39 1.9
## elegant 11 0.53 0.58 0.621 0.38 2.0
## inviting 18 0.52 0.53 0.543 0.46 2.0
## cluttered 7 -0.01 0.26 0.067 0.93 1.0
##
## PA1 PA2
## SS loadings 10.86 7.26
## Proportion Var 0.35 0.23
## Cumulative Var 0.35 0.58
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.92
## Multiple R square of scores with factors 0.90 0.85
## Minimum correlation of possible factor scores 0.80 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.90 -0.10 0.692 0.31 1.0
## beautiful 5 0.88 -0.07 0.697 0.30 1.0
## artistic 2 0.84 -0.25 0.465 0.54 1.2
## attractive 3 0.84 0.00 0.706 0.29 1.0
## fascinating 15 0.82 -0.02 0.640 0.36 1.0
## creative 9 0.78 -0.17 0.443 0.56 1.1
## appealing 1 0.76 0.13 0.730 0.27 1.1
## nice 22 0.75 0.12 0.696 0.30 1.0
## enjoyable 13 0.73 0.18 0.751 0.25 1.1
## pleasing 24 0.70 0.23 0.778 0.22 1.2
## exciting 14 0.68 0.12 0.595 0.40 1.1
## likable 19 0.64 0.28 0.752 0.25 1.4
## interesting 17 0.64 0.14 0.553 0.45 1.1
## lovely 20 0.62 0.25 0.670 0.33 1.3
## delightful 10 0.55 0.36 0.715 0.29 1.7
## tasteful 30 0.52 0.24 0.517 0.48 1.4
## colorHarmonious 8 0.51 0.16 0.406 0.59 1.2
## satisfying 28 0.48 0.42 0.701 0.30 2.0
## engaging 12 0.41 0.40 0.559 0.44 2.0
## provoking 27 0.38 -0.09 0.101 0.90 1.1
## sophisticated 29 0.36 0.33 0.407 0.59 2.0
## organized 23 -0.03 0.88 0.732 0.27 1.0
## clean 6 -0.04 0.79 0.568 0.43 1.0
## professional 26 -0.07 0.78 0.530 0.47 1.0
## balanced 4 0.09 0.74 0.654 0.35 1.0
## harmonious 16 0.24 0.58 0.607 0.39 1.3
## motivating 21 0.31 0.53 0.617 0.38 1.6
## wellDesigned 31 0.33 0.51 0.614 0.39 1.7
## elegant 11 0.37 0.47 0.621 0.38 1.9
## inviting 18 0.39 0.41 0.543 0.46 2.0
## cluttered 7 -0.17 0.35 0.067 0.93 1.4
##
## PA1 PA2
## SS loadings 11.66 6.47
## Proportion Var 0.38 0.21
## Cumulative Var 0.38 0.58
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.93 0.87
## Warning in readfun(f, ...): libpng warning: iCCP: known incorrect sRGB profile
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.88 0.774 0.23 1
## likable 19 0.87 0.752 0.25 1
## enjoyable 13 0.86 0.741 0.26 1
## delightful 10 0.85 0.716 0.28 1
## appealing 1 0.84 0.711 0.29 1
## satisfying 28 0.83 0.696 0.30 1
## nice 22 0.82 0.677 0.32 1
## lovely 20 0.82 0.670 0.33 1
## attractive 3 0.81 0.658 0.34 1
## beautiful 5 0.79 0.626 0.37 1
## pretty 25 0.78 0.607 0.39 1
## elegant 11 0.78 0.604 0.40 1
## wellDesigned 31 0.77 0.589 0.41 1
## fascinating 15 0.77 0.588 0.41 1
## motivating 21 0.77 0.587 0.41 1
## exciting 14 0.76 0.582 0.42 1
## harmonious 16 0.75 0.559 0.44 1
## engaging 12 0.74 0.553 0.45 1
## interesting 17 0.74 0.544 0.46 1
## organized 23 0.74 0.541 0.46 1
## balanced 4 0.73 0.539 0.46 1
## inviting 18 0.73 0.535 0.47 1
## tasteful 30 0.72 0.518 0.48 1
## clean 6 0.64 0.413 0.59 1
## sophisticated 29 0.63 0.403 0.60 1
## colorHarmonious 8 0.63 0.403 0.60 1
## professional 26 0.61 0.374 0.63 1
## creative 9 0.60 0.362 0.64 1
## artistic 2 0.59 0.347 0.65 1
## provoking 27 0.28 0.081 0.92 1
## cluttered 7 0.15 0.022 0.98 1
##
## PA1
## SS loadings 16.77
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 434 and the objective function was 5.73
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.26 0.692 0.31 1.2
## beautiful 5 0.78 0.29 0.697 0.30 1.3
## attractive 3 0.77 0.33 0.706 0.29 1.4
## appealing 1 0.75 0.41 0.730 0.27 1.6
## fascinating 15 0.74 0.30 0.640 0.36 1.3
## enjoyable 13 0.74 0.45 0.751 0.25 1.7
## pleasing 24 0.73 0.49 0.778 0.22 1.7
## nice 22 0.73 0.40 0.696 0.30 1.6
## likable 19 0.70 0.51 0.752 0.25 1.8
## artistic 2 0.67 0.10 0.465 0.54 1.0
## exciting 14 0.67 0.38 0.595 0.40 1.6
## lovely 20 0.67 0.48 0.670 0.33 1.8
## creative 9 0.65 0.15 0.443 0.56 1.1
## delightful 10 0.64 0.55 0.715 0.29 1.9
## interesting 17 0.64 0.38 0.553 0.45 1.6
## satisfying 28 0.61 0.58 0.701 0.30 2.0
## tasteful 30 0.58 0.43 0.517 0.48 1.8
## colorHarmonious 8 0.53 0.35 0.406 0.59 1.7
## engaging 12 0.53 0.53 0.559 0.44 2.0
## sophisticated 29 0.46 0.44 0.407 0.59 2.0
## provoking 27 0.31 0.06 0.101 0.90 1.1
## organized 23 0.32 0.79 0.732 0.27 1.3
## balanced 4 0.38 0.72 0.654 0.35 1.5
## clean 6 0.27 0.70 0.568 0.43 1.3
## professional 26 0.24 0.69 0.530 0.47 1.2
## harmonious 16 0.45 0.63 0.607 0.39 1.8
## motivating 21 0.50 0.61 0.617 0.38 1.9
## wellDesigned 31 0.51 0.60 0.614 0.39 1.9
## elegant 11 0.53 0.58 0.621 0.38 2.0
## inviting 18 0.52 0.53 0.543 0.46 2.0
## cluttered 7 -0.01 0.26 0.067 0.93 1.0
##
## PA1 PA2
## SS loadings 10.86 7.26
## Proportion Var 0.35 0.23
## Cumulative Var 0.35 0.58
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.92
## Multiple R square of scores with factors 0.90 0.85
## Minimum correlation of possible factor scores 0.80 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.90 -0.10 0.692 0.31 1.0
## beautiful 5 0.88 -0.07 0.697 0.30 1.0
## artistic 2 0.84 -0.25 0.465 0.54 1.2
## attractive 3 0.84 0.00 0.706 0.29 1.0
## fascinating 15 0.82 -0.02 0.640 0.36 1.0
## creative 9 0.78 -0.17 0.443 0.56 1.1
## appealing 1 0.76 0.13 0.730 0.27 1.1
## nice 22 0.75 0.12 0.696 0.30 1.0
## enjoyable 13 0.73 0.18 0.751 0.25 1.1
## pleasing 24 0.70 0.23 0.778 0.22 1.2
## exciting 14 0.68 0.12 0.595 0.40 1.1
## likable 19 0.64 0.28 0.752 0.25 1.4
## interesting 17 0.64 0.14 0.553 0.45 1.1
## lovely 20 0.62 0.25 0.670 0.33 1.3
## delightful 10 0.55 0.36 0.715 0.29 1.7
## tasteful 30 0.52 0.24 0.517 0.48 1.4
## colorHarmonious 8 0.51 0.16 0.406 0.59 1.2
## satisfying 28 0.48 0.42 0.701 0.30 2.0
## engaging 12 0.41 0.40 0.559 0.44 2.0
## provoking 27 0.38 -0.09 0.101 0.90 1.1
## sophisticated 29 0.36 0.33 0.407 0.59 2.0
## organized 23 -0.03 0.88 0.732 0.27 1.0
## clean 6 -0.04 0.79 0.568 0.43 1.0
## professional 26 -0.07 0.78 0.530 0.47 1.0
## balanced 4 0.09 0.74 0.654 0.35 1.0
## harmonious 16 0.24 0.58 0.607 0.39 1.3
## motivating 21 0.31 0.53 0.617 0.38 1.6
## wellDesigned 31 0.33 0.51 0.614 0.39 1.7
## elegant 11 0.37 0.47 0.621 0.38 1.9
## inviting 18 0.39 0.41 0.543 0.46 2.0
## cluttered 7 -0.17 0.35 0.067 0.93 1.4
##
## PA1 PA2
## SS loadings 11.66 6.47
## Proportion Var 0.38 0.21
## Cumulative Var 0.38 0.58
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.93 0.87
## Warning in readfun(f, ...): libpng warning: iCCP: known incorrect sRGB profile
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.88 0.774 0.23 1
## likable 19 0.87 0.752 0.25 1
## enjoyable 13 0.86 0.741 0.26 1
## delightful 10 0.85 0.716 0.28 1
## appealing 1 0.84 0.711 0.29 1
## satisfying 28 0.83 0.696 0.30 1
## nice 22 0.82 0.677 0.32 1
## lovely 20 0.82 0.670 0.33 1
## attractive 3 0.81 0.658 0.34 1
## beautiful 5 0.79 0.626 0.37 1
## pretty 25 0.78 0.607 0.39 1
## elegant 11 0.78 0.604 0.40 1
## wellDesigned 31 0.77 0.589 0.41 1
## fascinating 15 0.77 0.588 0.41 1
## motivating 21 0.77 0.587 0.41 1
## exciting 14 0.76 0.582 0.42 1
## harmonious 16 0.75 0.559 0.44 1
## engaging 12 0.74 0.553 0.45 1
## interesting 17 0.74 0.544 0.46 1
## organized 23 0.74 0.541 0.46 1
## balanced 4 0.73 0.539 0.46 1
## inviting 18 0.73 0.535 0.47 1
## tasteful 30 0.72 0.518 0.48 1
## clean 6 0.64 0.413 0.59 1
## sophisticated 29 0.63 0.403 0.60 1
## colorHarmonious 8 0.63 0.403 0.60 1
## professional 26 0.61 0.374 0.63 1
## creative 9 0.60 0.362 0.64 1
## artistic 2 0.59 0.347 0.65 1
## provoking 27 0.28 0.081 0.92 1
## cluttered 7 0.15 0.022 0.98 1
##
## PA1
## SS loadings 16.77
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 434 and the objective function was 5.73
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.26 0.692 0.31 1.2
## beautiful 5 0.78 0.29 0.697 0.30 1.3
## attractive 3 0.77 0.33 0.706 0.29 1.4
## appealing 1 0.75 0.41 0.730 0.27 1.6
## fascinating 15 0.74 0.30 0.640 0.36 1.3
## enjoyable 13 0.74 0.45 0.751 0.25 1.7
## pleasing 24 0.73 0.49 0.778 0.22 1.7
## nice 22 0.73 0.40 0.696 0.30 1.6
## likable 19 0.70 0.51 0.752 0.25 1.8
## artistic 2 0.67 0.10 0.465 0.54 1.0
## exciting 14 0.67 0.38 0.595 0.40 1.6
## lovely 20 0.67 0.48 0.670 0.33 1.8
## creative 9 0.65 0.15 0.443 0.56 1.1
## delightful 10 0.64 0.55 0.715 0.29 1.9
## interesting 17 0.64 0.38 0.553 0.45 1.6
## satisfying 28 0.61 0.58 0.701 0.30 2.0
## tasteful 30 0.58 0.43 0.517 0.48 1.8
## colorHarmonious 8 0.53 0.35 0.406 0.59 1.7
## engaging 12 0.53 0.53 0.559 0.44 2.0
## sophisticated 29 0.46 0.44 0.407 0.59 2.0
## provoking 27 0.31 0.06 0.101 0.90 1.1
## organized 23 0.32 0.79 0.732 0.27 1.3
## balanced 4 0.38 0.72 0.654 0.35 1.5
## clean 6 0.27 0.70 0.568 0.43 1.3
## professional 26 0.24 0.69 0.530 0.47 1.2
## harmonious 16 0.45 0.63 0.607 0.39 1.8
## motivating 21 0.50 0.61 0.617 0.38 1.9
## wellDesigned 31 0.51 0.60 0.614 0.39 1.9
## elegant 11 0.53 0.58 0.621 0.38 2.0
## inviting 18 0.52 0.53 0.543 0.46 2.0
## cluttered 7 -0.01 0.26 0.067 0.93 1.0
##
## PA1 PA2
## SS loadings 10.86 7.26
## Proportion Var 0.35 0.23
## Cumulative Var 0.35 0.58
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.92
## Multiple R square of scores with factors 0.90 0.85
## Minimum correlation of possible factor scores 0.80 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.90 -0.10 0.692 0.31 1.0
## beautiful 5 0.88 -0.07 0.697 0.30 1.0
## artistic 2 0.84 -0.25 0.465 0.54 1.2
## attractive 3 0.84 0.00 0.706 0.29 1.0
## fascinating 15 0.82 -0.02 0.640 0.36 1.0
## creative 9 0.78 -0.17 0.443 0.56 1.1
## appealing 1 0.76 0.13 0.730 0.27 1.1
## nice 22 0.75 0.12 0.696 0.30 1.0
## enjoyable 13 0.73 0.18 0.751 0.25 1.1
## pleasing 24 0.70 0.23 0.778 0.22 1.2
## exciting 14 0.68 0.12 0.595 0.40 1.1
## likable 19 0.64 0.28 0.752 0.25 1.4
## interesting 17 0.64 0.14 0.553 0.45 1.1
## lovely 20 0.62 0.25 0.670 0.33 1.3
## delightful 10 0.55 0.36 0.715 0.29 1.7
## tasteful 30 0.52 0.24 0.517 0.48 1.4
## colorHarmonious 8 0.51 0.16 0.406 0.59 1.2
## satisfying 28 0.48 0.42 0.701 0.30 2.0
## engaging 12 0.41 0.40 0.559 0.44 2.0
## provoking 27 0.38 -0.09 0.101 0.90 1.1
## sophisticated 29 0.36 0.33 0.407 0.59 2.0
## organized 23 -0.03 0.88 0.732 0.27 1.0
## clean 6 -0.04 0.79 0.568 0.43 1.0
## professional 26 -0.07 0.78 0.530 0.47 1.0
## balanced 4 0.09 0.74 0.654 0.35 1.0
## harmonious 16 0.24 0.58 0.607 0.39 1.3
## motivating 21 0.31 0.53 0.617 0.38 1.6
## wellDesigned 31 0.33 0.51 0.614 0.39 1.7
## elegant 11 0.37 0.47 0.621 0.38 1.9
## inviting 18 0.39 0.41 0.543 0.46 2.0
## cluttered 7 -0.17 0.35 0.067 0.93 1.4
##
## PA1 PA2
## SS loadings 11.66 6.47
## Proportion Var 0.38 0.21
## Cumulative Var 0.38 0.58
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.93 0.87
## Warning in readfun(f, ...): libpng warning: iCCP: known incorrect sRGB profile
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.88 0.774 0.23 1
## likable 19 0.87 0.752 0.25 1
## enjoyable 13 0.86 0.741 0.26 1
## delightful 10 0.85 0.716 0.28 1
## appealing 1 0.84 0.711 0.29 1
## satisfying 28 0.83 0.696 0.30 1
## nice 22 0.82 0.677 0.32 1
## lovely 20 0.82 0.670 0.33 1
## attractive 3 0.81 0.658 0.34 1
## beautiful 5 0.79 0.626 0.37 1
## pretty 25 0.78 0.607 0.39 1
## elegant 11 0.78 0.604 0.40 1
## wellDesigned 31 0.77 0.589 0.41 1
## fascinating 15 0.77 0.588 0.41 1
## motivating 21 0.77 0.587 0.41 1
## exciting 14 0.76 0.582 0.42 1
## harmonious 16 0.75 0.559 0.44 1
## engaging 12 0.74 0.553 0.45 1
## interesting 17 0.74 0.544 0.46 1
## organized 23 0.74 0.541 0.46 1
## balanced 4 0.73 0.539 0.46 1
## inviting 18 0.73 0.535 0.47 1
## tasteful 30 0.72 0.518 0.48 1
## clean 6 0.64 0.413 0.59 1
## sophisticated 29 0.63 0.403 0.60 1
## colorHarmonious 8 0.63 0.403 0.60 1
## professional 26 0.61 0.374 0.63 1
## creative 9 0.60 0.362 0.64 1
## artistic 2 0.59 0.347 0.65 1
## provoking 27 0.28 0.081 0.92 1
## cluttered 7 0.15 0.022 0.98 1
##
## PA1
## SS loadings 16.77
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 434 and the objective function was 5.73
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.26 0.692 0.31 1.2
## beautiful 5 0.78 0.29 0.697 0.30 1.3
## attractive 3 0.77 0.33 0.706 0.29 1.4
## appealing 1 0.75 0.41 0.730 0.27 1.6
## fascinating 15 0.74 0.30 0.640 0.36 1.3
## enjoyable 13 0.74 0.45 0.751 0.25 1.7
## pleasing 24 0.73 0.49 0.778 0.22 1.7
## nice 22 0.73 0.40 0.696 0.30 1.6
## likable 19 0.70 0.51 0.752 0.25 1.8
## artistic 2 0.67 0.10 0.465 0.54 1.0
## exciting 14 0.67 0.38 0.595 0.40 1.6
## lovely 20 0.67 0.48 0.670 0.33 1.8
## creative 9 0.65 0.15 0.443 0.56 1.1
## delightful 10 0.64 0.55 0.715 0.29 1.9
## interesting 17 0.64 0.38 0.553 0.45 1.6
## satisfying 28 0.61 0.58 0.701 0.30 2.0
## tasteful 30 0.58 0.43 0.517 0.48 1.8
## colorHarmonious 8 0.53 0.35 0.406 0.59 1.7
## engaging 12 0.53 0.53 0.559 0.44 2.0
## sophisticated 29 0.46 0.44 0.407 0.59 2.0
## provoking 27 0.31 0.06 0.101 0.90 1.1
## organized 23 0.32 0.79 0.732 0.27 1.3
## balanced 4 0.38 0.72 0.654 0.35 1.5
## clean 6 0.27 0.70 0.568 0.43 1.3
## professional 26 0.24 0.69 0.530 0.47 1.2
## harmonious 16 0.45 0.63 0.607 0.39 1.8
## motivating 21 0.50 0.61 0.617 0.38 1.9
## wellDesigned 31 0.51 0.60 0.614 0.39 1.9
## elegant 11 0.53 0.58 0.621 0.38 2.0
## inviting 18 0.52 0.53 0.543 0.46 2.0
## cluttered 7 -0.01 0.26 0.067 0.93 1.0
##
## PA1 PA2
## SS loadings 10.86 7.26
## Proportion Var 0.35 0.23
## Cumulative Var 0.35 0.58
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.92
## Multiple R square of scores with factors 0.90 0.85
## Minimum correlation of possible factor scores 0.80 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.90 -0.10 0.692 0.31 1.0
## beautiful 5 0.88 -0.07 0.697 0.30 1.0
## artistic 2 0.84 -0.25 0.465 0.54 1.2
## attractive 3 0.84 0.00 0.706 0.29 1.0
## fascinating 15 0.82 -0.02 0.640 0.36 1.0
## creative 9 0.78 -0.17 0.443 0.56 1.1
## appealing 1 0.76 0.13 0.730 0.27 1.1
## nice 22 0.75 0.12 0.696 0.30 1.0
## enjoyable 13 0.73 0.18 0.751 0.25 1.1
## pleasing 24 0.70 0.23 0.778 0.22 1.2
## exciting 14 0.68 0.12 0.595 0.40 1.1
## likable 19 0.64 0.28 0.752 0.25 1.4
## interesting 17 0.64 0.14 0.553 0.45 1.1
## lovely 20 0.62 0.25 0.670 0.33 1.3
## delightful 10 0.55 0.36 0.715 0.29 1.7
## tasteful 30 0.52 0.24 0.517 0.48 1.4
## colorHarmonious 8 0.51 0.16 0.406 0.59 1.2
## satisfying 28 0.48 0.42 0.701 0.30 2.0
## engaging 12 0.41 0.40 0.559 0.44 2.0
## provoking 27 0.38 -0.09 0.101 0.90 1.1
## sophisticated 29 0.36 0.33 0.407 0.59 2.0
## organized 23 -0.03 0.88 0.732 0.27 1.0
## clean 6 -0.04 0.79 0.568 0.43 1.0
## professional 26 -0.07 0.78 0.530 0.47 1.0
## balanced 4 0.09 0.74 0.654 0.35 1.0
## harmonious 16 0.24 0.58 0.607 0.39 1.3
## motivating 21 0.31 0.53 0.617 0.38 1.6
## wellDesigned 31 0.33 0.51 0.614 0.39 1.7
## elegant 11 0.37 0.47 0.621 0.38 1.9
## inviting 18 0.39 0.41 0.543 0.46 2.0
## cluttered 7 -0.17 0.35 0.067 0.93 1.4
##
## PA1 PA2
## SS loadings 11.66 6.47
## Proportion Var 0.38 0.21
## Cumulative Var 0.38 0.58
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.05
## The degrees of freedom for the model are 404 and the objective function was 4.16
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.93 0.87
##
##
## ## Image 5
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.89 0.792 0.21 1
## nice 22 0.87 0.766 0.23 1
## appealing 1 0.87 0.750 0.25 1
## likable 19 0.86 0.746 0.25 1
## enjoyable 13 0.86 0.746 0.25 1
## attractive 3 0.86 0.743 0.26 1
## satisfying 28 0.85 0.725 0.28 1
## beautiful 5 0.84 0.698 0.30 1
## delightful 10 0.83 0.689 0.31 1
## motivating 21 0.83 0.685 0.31 1
## inviting 18 0.82 0.675 0.32 1
## harmonious 16 0.82 0.675 0.33 1
## exciting 14 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.657 0.34 1
## pretty 25 0.81 0.652 0.35 1
## lovely 20 0.80 0.637 0.36 1
## engaging 12 0.78 0.613 0.39 1
## tasteful 30 0.77 0.587 0.41 1
## interesting 17 0.76 0.577 0.42 1
## elegant 11 0.74 0.544 0.46 1
## balanced 4 0.71 0.510 0.49 1
## clean 6 0.70 0.489 0.51 1
## fascinating 15 0.70 0.486 0.51 1
## organized 23 0.67 0.454 0.55 1
## creative 9 0.67 0.450 0.55 1
## artistic 2 0.66 0.432 0.57 1
## colorHarmonious 8 0.64 0.405 0.59 1
## professional 26 0.62 0.382 0.62 1
## sophisticated 29 0.61 0.368 0.63 1
## cluttered 7 0.39 0.150 0.85 1
## provoking 27 0.28 0.079 0.92 1
##
## PA1
## SS loadings 17.83
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 434 and the objective function was 5.71
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.35 0.737 0.26 1.4
## fascinating 15 0.78 0.18 0.637 0.36 1.1
## beautiful 5 0.77 0.39 0.747 0.25 1.5
## interesting 17 0.76 0.29 0.664 0.34 1.3
## attractive 3 0.72 0.49 0.756 0.24 1.8
## enjoyable 13 0.71 0.50 0.754 0.25 1.8
## pretty 25 0.70 0.43 0.674 0.33 1.7
## creative 9 0.70 0.23 0.537 0.46 1.2
## artistic 2 0.69 0.21 0.527 0.47 1.2
## likable 19 0.68 0.54 0.747 0.25 1.9
## appealing 1 0.67 0.55 0.749 0.25 1.9
## satisfying 28 0.66 0.54 0.724 0.28 1.9
## nice 22 0.65 0.59 0.764 0.24 2.0
## pleasing 24 0.64 0.62 0.791 0.21 2.0
## lovely 20 0.63 0.49 0.639 0.36 1.9
## motivating 21 0.63 0.53 0.684 0.32 1.9
## delightful 10 0.63 0.54 0.687 0.31 2.0
## engaging 12 0.62 0.48 0.615 0.38 1.9
## provoking 27 0.30 0.09 0.096 0.90 1.2
## organized 23 0.17 0.84 0.733 0.27 1.1
## clean 6 0.25 0.78 0.674 0.33 1.2
## balanced 4 0.30 0.74 0.641 0.36 1.3
## wellDesigned 31 0.46 0.70 0.704 0.30 1.7
## professional 26 0.25 0.66 0.493 0.51 1.3
## harmonious 16 0.52 0.65 0.695 0.31 1.9
## inviting 18 0.54 0.63 0.688 0.31 1.9
## elegant 11 0.46 0.60 0.564 0.44 1.9
## tasteful 30 0.53 0.56 0.591 0.41 2.0
## colorHarmonious 8 0.43 0.47 0.408 0.59 2.0
## sophisticated 29 0.41 0.45 0.371 0.63 2.0
## cluttered 7 0.15 0.41 0.194 0.81 1.3
##
## PA1 PA2
## SS loadings 10.60 8.69
## Proportion Var 0.34 0.28
## Cumulative Var 0.34 0.62
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.91 0.89
## Minimum correlation of possible factor scores 0.81 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## fascinating 15 0.97 -0.25 0.637 0.36 1.1
## exciting 14 0.88 -0.03 0.737 0.26 1.0
## interesting 17 0.88 -0.09 0.664 0.34 1.0
## artistic 2 0.84 -0.15 0.527 0.47 1.1
## creative 9 0.83 -0.13 0.537 0.46 1.0
## beautiful 5 0.82 0.05 0.747 0.25 1.0
## pretty 25 0.71 0.14 0.674 0.33 1.1
## attractive 3 0.70 0.21 0.756 0.24 1.2
## enjoyable 13 0.67 0.24 0.754 0.25 1.3
## likable 19 0.60 0.32 0.747 0.25 1.5
## appealing 1 0.58 0.34 0.749 0.25 1.6
## satisfying 28 0.57 0.33 0.724 0.28 1.6
## lovely 20 0.57 0.27 0.639 0.36 1.4
## engaging 12 0.56 0.26 0.615 0.38 1.4
## motivating 21 0.54 0.34 0.684 0.32 1.7
## delightful 10 0.53 0.35 0.687 0.31 1.7
## nice 22 0.53 0.40 0.764 0.24 1.9
## pleasing 24 0.50 0.45 0.791 0.21 2.0
## provoking 27 0.36 -0.07 0.096 0.90 1.1
## organized 23 -0.31 1.07 0.733 0.27 1.2
## clean 6 -0.16 0.94 0.674 0.33 1.1
## balanced 4 -0.06 0.84 0.641 0.36 1.0
## professional 26 -0.08 0.76 0.493 0.51 1.0
## wellDesigned 31 0.20 0.68 0.704 0.30 1.2
## harmonious 16 0.30 0.58 0.695 0.31 1.5
## elegant 11 0.25 0.54 0.564 0.44 1.4
## inviting 18 0.34 0.54 0.688 0.31 1.7
## cluttered 7 -0.06 0.48 0.194 0.81 1.0
## tasteful 30 0.38 0.44 0.591 0.41 1.9
## colorHarmonious 8 0.31 0.37 0.408 0.59 1.9
## sophisticated 29 0.29 0.36 0.371 0.63 1.9
##
## PA1 PA2
## SS loadings 11.11 8.18
## Proportion Var 0.36 0.26
## Cumulative Var 0.36 0.62
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.97 0.96
## Minimum correlation of possible factor scores 0.94 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.89 0.792 0.21 1
## nice 22 0.87 0.766 0.23 1
## appealing 1 0.87 0.750 0.25 1
## likable 19 0.86 0.746 0.25 1
## enjoyable 13 0.86 0.746 0.25 1
## attractive 3 0.86 0.743 0.26 1
## satisfying 28 0.85 0.725 0.28 1
## beautiful 5 0.84 0.698 0.30 1
## delightful 10 0.83 0.689 0.31 1
## motivating 21 0.83 0.685 0.31 1
## inviting 18 0.82 0.675 0.32 1
## harmonious 16 0.82 0.675 0.33 1
## exciting 14 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.657 0.34 1
## pretty 25 0.81 0.652 0.35 1
## lovely 20 0.80 0.637 0.36 1
## engaging 12 0.78 0.613 0.39 1
## tasteful 30 0.77 0.587 0.41 1
## interesting 17 0.76 0.577 0.42 1
## elegant 11 0.74 0.544 0.46 1
## balanced 4 0.71 0.510 0.49 1
## clean 6 0.70 0.489 0.51 1
## fascinating 15 0.70 0.486 0.51 1
## organized 23 0.67 0.454 0.55 1
## creative 9 0.67 0.450 0.55 1
## artistic 2 0.66 0.432 0.57 1
## colorHarmonious 8 0.64 0.405 0.59 1
## professional 26 0.62 0.382 0.62 1
## sophisticated 29 0.61 0.368 0.63 1
## cluttered 7 0.39 0.150 0.85 1
## provoking 27 0.28 0.079 0.92 1
##
## PA1
## SS loadings 17.83
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 434 and the objective function was 5.71
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.35 0.737 0.26 1.4
## fascinating 15 0.78 0.18 0.637 0.36 1.1
## beautiful 5 0.77 0.39 0.747 0.25 1.5
## interesting 17 0.76 0.29 0.664 0.34 1.3
## attractive 3 0.72 0.49 0.756 0.24 1.8
## enjoyable 13 0.71 0.50 0.754 0.25 1.8
## pretty 25 0.70 0.43 0.674 0.33 1.7
## creative 9 0.70 0.23 0.537 0.46 1.2
## artistic 2 0.69 0.21 0.527 0.47 1.2
## likable 19 0.68 0.54 0.747 0.25 1.9
## appealing 1 0.67 0.55 0.749 0.25 1.9
## satisfying 28 0.66 0.54 0.724 0.28 1.9
## nice 22 0.65 0.59 0.764 0.24 2.0
## pleasing 24 0.64 0.62 0.791 0.21 2.0
## lovely 20 0.63 0.49 0.639 0.36 1.9
## motivating 21 0.63 0.53 0.684 0.32 1.9
## delightful 10 0.63 0.54 0.687 0.31 2.0
## engaging 12 0.62 0.48 0.615 0.38 1.9
## provoking 27 0.30 0.09 0.096 0.90 1.2
## organized 23 0.17 0.84 0.733 0.27 1.1
## clean 6 0.25 0.78 0.674 0.33 1.2
## balanced 4 0.30 0.74 0.641 0.36 1.3
## wellDesigned 31 0.46 0.70 0.704 0.30 1.7
## professional 26 0.25 0.66 0.493 0.51 1.3
## harmonious 16 0.52 0.65 0.695 0.31 1.9
## inviting 18 0.54 0.63 0.688 0.31 1.9
## elegant 11 0.46 0.60 0.564 0.44 1.9
## tasteful 30 0.53 0.56 0.591 0.41 2.0
## colorHarmonious 8 0.43 0.47 0.408 0.59 2.0
## sophisticated 29 0.41 0.45 0.371 0.63 2.0
## cluttered 7 0.15 0.41 0.194 0.81 1.3
##
## PA1 PA2
## SS loadings 10.60 8.69
## Proportion Var 0.34 0.28
## Cumulative Var 0.34 0.62
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.91 0.89
## Minimum correlation of possible factor scores 0.81 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## fascinating 15 0.97 -0.25 0.637 0.36 1.1
## exciting 14 0.88 -0.03 0.737 0.26 1.0
## interesting 17 0.88 -0.09 0.664 0.34 1.0
## artistic 2 0.84 -0.15 0.527 0.47 1.1
## creative 9 0.83 -0.13 0.537 0.46 1.0
## beautiful 5 0.82 0.05 0.747 0.25 1.0
## pretty 25 0.71 0.14 0.674 0.33 1.1
## attractive 3 0.70 0.21 0.756 0.24 1.2
## enjoyable 13 0.67 0.24 0.754 0.25 1.3
## likable 19 0.60 0.32 0.747 0.25 1.5
## appealing 1 0.58 0.34 0.749 0.25 1.6
## satisfying 28 0.57 0.33 0.724 0.28 1.6
## lovely 20 0.57 0.27 0.639 0.36 1.4
## engaging 12 0.56 0.26 0.615 0.38 1.4
## motivating 21 0.54 0.34 0.684 0.32 1.7
## delightful 10 0.53 0.35 0.687 0.31 1.7
## nice 22 0.53 0.40 0.764 0.24 1.9
## pleasing 24 0.50 0.45 0.791 0.21 2.0
## provoking 27 0.36 -0.07 0.096 0.90 1.1
## organized 23 -0.31 1.07 0.733 0.27 1.2
## clean 6 -0.16 0.94 0.674 0.33 1.1
## balanced 4 -0.06 0.84 0.641 0.36 1.0
## professional 26 -0.08 0.76 0.493 0.51 1.0
## wellDesigned 31 0.20 0.68 0.704 0.30 1.2
## harmonious 16 0.30 0.58 0.695 0.31 1.5
## elegant 11 0.25 0.54 0.564 0.44 1.4
## inviting 18 0.34 0.54 0.688 0.31 1.7
## cluttered 7 -0.06 0.48 0.194 0.81 1.0
## tasteful 30 0.38 0.44 0.591 0.41 1.9
## colorHarmonious 8 0.31 0.37 0.408 0.59 1.9
## sophisticated 29 0.29 0.36 0.371 0.63 1.9
##
## PA1 PA2
## SS loadings 11.11 8.18
## Proportion Var 0.36 0.26
## Cumulative Var 0.36 0.62
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.97 0.96
## Minimum correlation of possible factor scores 0.94 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.89 0.792 0.21 1
## nice 22 0.87 0.766 0.23 1
## appealing 1 0.87 0.750 0.25 1
## likable 19 0.86 0.746 0.25 1
## enjoyable 13 0.86 0.746 0.25 1
## attractive 3 0.86 0.743 0.26 1
## satisfying 28 0.85 0.725 0.28 1
## beautiful 5 0.84 0.698 0.30 1
## delightful 10 0.83 0.689 0.31 1
## motivating 21 0.83 0.685 0.31 1
## inviting 18 0.82 0.675 0.32 1
## harmonious 16 0.82 0.675 0.33 1
## exciting 14 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.657 0.34 1
## pretty 25 0.81 0.652 0.35 1
## lovely 20 0.80 0.637 0.36 1
## engaging 12 0.78 0.613 0.39 1
## tasteful 30 0.77 0.587 0.41 1
## interesting 17 0.76 0.577 0.42 1
## elegant 11 0.74 0.544 0.46 1
## balanced 4 0.71 0.510 0.49 1
## clean 6 0.70 0.489 0.51 1
## fascinating 15 0.70 0.486 0.51 1
## organized 23 0.67 0.454 0.55 1
## creative 9 0.67 0.450 0.55 1
## artistic 2 0.66 0.432 0.57 1
## colorHarmonious 8 0.64 0.405 0.59 1
## professional 26 0.62 0.382 0.62 1
## sophisticated 29 0.61 0.368 0.63 1
## cluttered 7 0.39 0.150 0.85 1
## provoking 27 0.28 0.079 0.92 1
##
## PA1
## SS loadings 17.83
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 434 and the objective function was 5.71
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.35 0.737 0.26 1.4
## fascinating 15 0.78 0.18 0.637 0.36 1.1
## beautiful 5 0.77 0.39 0.747 0.25 1.5
## interesting 17 0.76 0.29 0.664 0.34 1.3
## attractive 3 0.72 0.49 0.756 0.24 1.8
## enjoyable 13 0.71 0.50 0.754 0.25 1.8
## pretty 25 0.70 0.43 0.674 0.33 1.7
## creative 9 0.70 0.23 0.537 0.46 1.2
## artistic 2 0.69 0.21 0.527 0.47 1.2
## likable 19 0.68 0.54 0.747 0.25 1.9
## appealing 1 0.67 0.55 0.749 0.25 1.9
## satisfying 28 0.66 0.54 0.724 0.28 1.9
## nice 22 0.65 0.59 0.764 0.24 2.0
## pleasing 24 0.64 0.62 0.791 0.21 2.0
## lovely 20 0.63 0.49 0.639 0.36 1.9
## motivating 21 0.63 0.53 0.684 0.32 1.9
## delightful 10 0.63 0.54 0.687 0.31 2.0
## engaging 12 0.62 0.48 0.615 0.38 1.9
## provoking 27 0.30 0.09 0.096 0.90 1.2
## organized 23 0.17 0.84 0.733 0.27 1.1
## clean 6 0.25 0.78 0.674 0.33 1.2
## balanced 4 0.30 0.74 0.641 0.36 1.3
## wellDesigned 31 0.46 0.70 0.704 0.30 1.7
## professional 26 0.25 0.66 0.493 0.51 1.3
## harmonious 16 0.52 0.65 0.695 0.31 1.9
## inviting 18 0.54 0.63 0.688 0.31 1.9
## elegant 11 0.46 0.60 0.564 0.44 1.9
## tasteful 30 0.53 0.56 0.591 0.41 2.0
## colorHarmonious 8 0.43 0.47 0.408 0.59 2.0
## sophisticated 29 0.41 0.45 0.371 0.63 2.0
## cluttered 7 0.15 0.41 0.194 0.81 1.3
##
## PA1 PA2
## SS loadings 10.60 8.69
## Proportion Var 0.34 0.28
## Cumulative Var 0.34 0.62
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.91 0.89
## Minimum correlation of possible factor scores 0.81 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## fascinating 15 0.97 -0.25 0.637 0.36 1.1
## exciting 14 0.88 -0.03 0.737 0.26 1.0
## interesting 17 0.88 -0.09 0.664 0.34 1.0
## artistic 2 0.84 -0.15 0.527 0.47 1.1
## creative 9 0.83 -0.13 0.537 0.46 1.0
## beautiful 5 0.82 0.05 0.747 0.25 1.0
## pretty 25 0.71 0.14 0.674 0.33 1.1
## attractive 3 0.70 0.21 0.756 0.24 1.2
## enjoyable 13 0.67 0.24 0.754 0.25 1.3
## likable 19 0.60 0.32 0.747 0.25 1.5
## appealing 1 0.58 0.34 0.749 0.25 1.6
## satisfying 28 0.57 0.33 0.724 0.28 1.6
## lovely 20 0.57 0.27 0.639 0.36 1.4
## engaging 12 0.56 0.26 0.615 0.38 1.4
## motivating 21 0.54 0.34 0.684 0.32 1.7
## delightful 10 0.53 0.35 0.687 0.31 1.7
## nice 22 0.53 0.40 0.764 0.24 1.9
## pleasing 24 0.50 0.45 0.791 0.21 2.0
## provoking 27 0.36 -0.07 0.096 0.90 1.1
## organized 23 -0.31 1.07 0.733 0.27 1.2
## clean 6 -0.16 0.94 0.674 0.33 1.1
## balanced 4 -0.06 0.84 0.641 0.36 1.0
## professional 26 -0.08 0.76 0.493 0.51 1.0
## wellDesigned 31 0.20 0.68 0.704 0.30 1.2
## harmonious 16 0.30 0.58 0.695 0.31 1.5
## elegant 11 0.25 0.54 0.564 0.44 1.4
## inviting 18 0.34 0.54 0.688 0.31 1.7
## cluttered 7 -0.06 0.48 0.194 0.81 1.0
## tasteful 30 0.38 0.44 0.591 0.41 1.9
## colorHarmonious 8 0.31 0.37 0.408 0.59 1.9
## sophisticated 29 0.29 0.36 0.371 0.63 1.9
##
## PA1 PA2
## SS loadings 11.11 8.18
## Proportion Var 0.36 0.26
## Cumulative Var 0.36 0.62
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.97 0.96
## Minimum correlation of possible factor scores 0.94 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.89 0.792 0.21 1
## nice 22 0.87 0.766 0.23 1
## appealing 1 0.87 0.750 0.25 1
## likable 19 0.86 0.746 0.25 1
## enjoyable 13 0.86 0.746 0.25 1
## attractive 3 0.86 0.743 0.26 1
## satisfying 28 0.85 0.725 0.28 1
## beautiful 5 0.84 0.698 0.30 1
## delightful 10 0.83 0.689 0.31 1
## motivating 21 0.83 0.685 0.31 1
## inviting 18 0.82 0.675 0.32 1
## harmonious 16 0.82 0.675 0.33 1
## exciting 14 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.657 0.34 1
## pretty 25 0.81 0.652 0.35 1
## lovely 20 0.80 0.637 0.36 1
## engaging 12 0.78 0.613 0.39 1
## tasteful 30 0.77 0.587 0.41 1
## interesting 17 0.76 0.577 0.42 1
## elegant 11 0.74 0.544 0.46 1
## balanced 4 0.71 0.510 0.49 1
## clean 6 0.70 0.489 0.51 1
## fascinating 15 0.70 0.486 0.51 1
## organized 23 0.67 0.454 0.55 1
## creative 9 0.67 0.450 0.55 1
## artistic 2 0.66 0.432 0.57 1
## colorHarmonious 8 0.64 0.405 0.59 1
## professional 26 0.62 0.382 0.62 1
## sophisticated 29 0.61 0.368 0.63 1
## cluttered 7 0.39 0.150 0.85 1
## provoking 27 0.28 0.079 0.92 1
##
## PA1
## SS loadings 17.83
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 434 and the objective function was 5.71
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.35 0.737 0.26 1.4
## fascinating 15 0.78 0.18 0.637 0.36 1.1
## beautiful 5 0.77 0.39 0.747 0.25 1.5
## interesting 17 0.76 0.29 0.664 0.34 1.3
## attractive 3 0.72 0.49 0.756 0.24 1.8
## enjoyable 13 0.71 0.50 0.754 0.25 1.8
## pretty 25 0.70 0.43 0.674 0.33 1.7
## creative 9 0.70 0.23 0.537 0.46 1.2
## artistic 2 0.69 0.21 0.527 0.47 1.2
## likable 19 0.68 0.54 0.747 0.25 1.9
## appealing 1 0.67 0.55 0.749 0.25 1.9
## satisfying 28 0.66 0.54 0.724 0.28 1.9
## nice 22 0.65 0.59 0.764 0.24 2.0
## pleasing 24 0.64 0.62 0.791 0.21 2.0
## lovely 20 0.63 0.49 0.639 0.36 1.9
## motivating 21 0.63 0.53 0.684 0.32 1.9
## delightful 10 0.63 0.54 0.687 0.31 2.0
## engaging 12 0.62 0.48 0.615 0.38 1.9
## provoking 27 0.30 0.09 0.096 0.90 1.2
## organized 23 0.17 0.84 0.733 0.27 1.1
## clean 6 0.25 0.78 0.674 0.33 1.2
## balanced 4 0.30 0.74 0.641 0.36 1.3
## wellDesigned 31 0.46 0.70 0.704 0.30 1.7
## professional 26 0.25 0.66 0.493 0.51 1.3
## harmonious 16 0.52 0.65 0.695 0.31 1.9
## inviting 18 0.54 0.63 0.688 0.31 1.9
## elegant 11 0.46 0.60 0.564 0.44 1.9
## tasteful 30 0.53 0.56 0.591 0.41 2.0
## colorHarmonious 8 0.43 0.47 0.408 0.59 2.0
## sophisticated 29 0.41 0.45 0.371 0.63 2.0
## cluttered 7 0.15 0.41 0.194 0.81 1.3
##
## PA1 PA2
## SS loadings 10.60 8.69
## Proportion Var 0.34 0.28
## Cumulative Var 0.34 0.62
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.91 0.89
## Minimum correlation of possible factor scores 0.81 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## fascinating 15 0.97 -0.25 0.637 0.36 1.1
## exciting 14 0.88 -0.03 0.737 0.26 1.0
## interesting 17 0.88 -0.09 0.664 0.34 1.0
## artistic 2 0.84 -0.15 0.527 0.47 1.1
## creative 9 0.83 -0.13 0.537 0.46 1.0
## beautiful 5 0.82 0.05 0.747 0.25 1.0
## pretty 25 0.71 0.14 0.674 0.33 1.1
## attractive 3 0.70 0.21 0.756 0.24 1.2
## enjoyable 13 0.67 0.24 0.754 0.25 1.3
## likable 19 0.60 0.32 0.747 0.25 1.5
## appealing 1 0.58 0.34 0.749 0.25 1.6
## satisfying 28 0.57 0.33 0.724 0.28 1.6
## lovely 20 0.57 0.27 0.639 0.36 1.4
## engaging 12 0.56 0.26 0.615 0.38 1.4
## motivating 21 0.54 0.34 0.684 0.32 1.7
## delightful 10 0.53 0.35 0.687 0.31 1.7
## nice 22 0.53 0.40 0.764 0.24 1.9
## pleasing 24 0.50 0.45 0.791 0.21 2.0
## provoking 27 0.36 -0.07 0.096 0.90 1.1
## organized 23 -0.31 1.07 0.733 0.27 1.2
## clean 6 -0.16 0.94 0.674 0.33 1.1
## balanced 4 -0.06 0.84 0.641 0.36 1.0
## professional 26 -0.08 0.76 0.493 0.51 1.0
## wellDesigned 31 0.20 0.68 0.704 0.30 1.2
## harmonious 16 0.30 0.58 0.695 0.31 1.5
## elegant 11 0.25 0.54 0.564 0.44 1.4
## inviting 18 0.34 0.54 0.688 0.31 1.7
## cluttered 7 -0.06 0.48 0.194 0.81 1.0
## tasteful 30 0.38 0.44 0.591 0.41 1.9
## colorHarmonious 8 0.31 0.37 0.408 0.59 1.9
## sophisticated 29 0.29 0.36 0.371 0.63 1.9
##
## PA1 PA2
## SS loadings 11.11 8.18
## Proportion Var 0.36 0.26
## Cumulative Var 0.36 0.62
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.97 0.96
## Minimum correlation of possible factor scores 0.94 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.89 0.792 0.21 1
## nice 22 0.87 0.766 0.23 1
## appealing 1 0.87 0.750 0.25 1
## likable 19 0.86 0.746 0.25 1
## enjoyable 13 0.86 0.746 0.25 1
## attractive 3 0.86 0.743 0.26 1
## satisfying 28 0.85 0.725 0.28 1
## beautiful 5 0.84 0.698 0.30 1
## delightful 10 0.83 0.689 0.31 1
## motivating 21 0.83 0.685 0.31 1
## inviting 18 0.82 0.675 0.32 1
## harmonious 16 0.82 0.675 0.33 1
## exciting 14 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.657 0.34 1
## pretty 25 0.81 0.652 0.35 1
## lovely 20 0.80 0.637 0.36 1
## engaging 12 0.78 0.613 0.39 1
## tasteful 30 0.77 0.587 0.41 1
## interesting 17 0.76 0.577 0.42 1
## elegant 11 0.74 0.544 0.46 1
## balanced 4 0.71 0.510 0.49 1
## clean 6 0.70 0.489 0.51 1
## fascinating 15 0.70 0.486 0.51 1
## organized 23 0.67 0.454 0.55 1
## creative 9 0.67 0.450 0.55 1
## artistic 2 0.66 0.432 0.57 1
## colorHarmonious 8 0.64 0.405 0.59 1
## professional 26 0.62 0.382 0.62 1
## sophisticated 29 0.61 0.368 0.63 1
## cluttered 7 0.39 0.150 0.85 1
## provoking 27 0.28 0.079 0.92 1
##
## PA1
## SS loadings 17.83
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 434 and the objective function was 5.71
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.35 0.737 0.26 1.4
## fascinating 15 0.78 0.18 0.637 0.36 1.1
## beautiful 5 0.77 0.39 0.747 0.25 1.5
## interesting 17 0.76 0.29 0.664 0.34 1.3
## attractive 3 0.72 0.49 0.756 0.24 1.8
## enjoyable 13 0.71 0.50 0.754 0.25 1.8
## pretty 25 0.70 0.43 0.674 0.33 1.7
## creative 9 0.70 0.23 0.537 0.46 1.2
## artistic 2 0.69 0.21 0.527 0.47 1.2
## likable 19 0.68 0.54 0.747 0.25 1.9
## appealing 1 0.67 0.55 0.749 0.25 1.9
## satisfying 28 0.66 0.54 0.724 0.28 1.9
## nice 22 0.65 0.59 0.764 0.24 2.0
## pleasing 24 0.64 0.62 0.791 0.21 2.0
## lovely 20 0.63 0.49 0.639 0.36 1.9
## motivating 21 0.63 0.53 0.684 0.32 1.9
## delightful 10 0.63 0.54 0.687 0.31 2.0
## engaging 12 0.62 0.48 0.615 0.38 1.9
## provoking 27 0.30 0.09 0.096 0.90 1.2
## organized 23 0.17 0.84 0.733 0.27 1.1
## clean 6 0.25 0.78 0.674 0.33 1.2
## balanced 4 0.30 0.74 0.641 0.36 1.3
## wellDesigned 31 0.46 0.70 0.704 0.30 1.7
## professional 26 0.25 0.66 0.493 0.51 1.3
## harmonious 16 0.52 0.65 0.695 0.31 1.9
## inviting 18 0.54 0.63 0.688 0.31 1.9
## elegant 11 0.46 0.60 0.564 0.44 1.9
## tasteful 30 0.53 0.56 0.591 0.41 2.0
## colorHarmonious 8 0.43 0.47 0.408 0.59 2.0
## sophisticated 29 0.41 0.45 0.371 0.63 2.0
## cluttered 7 0.15 0.41 0.194 0.81 1.3
##
## PA1 PA2
## SS loadings 10.60 8.69
## Proportion Var 0.34 0.28
## Cumulative Var 0.34 0.62
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.91 0.89
## Minimum correlation of possible factor scores 0.81 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## fascinating 15 0.97 -0.25 0.637 0.36 1.1
## exciting 14 0.88 -0.03 0.737 0.26 1.0
## interesting 17 0.88 -0.09 0.664 0.34 1.0
## artistic 2 0.84 -0.15 0.527 0.47 1.1
## creative 9 0.83 -0.13 0.537 0.46 1.0
## beautiful 5 0.82 0.05 0.747 0.25 1.0
## pretty 25 0.71 0.14 0.674 0.33 1.1
## attractive 3 0.70 0.21 0.756 0.24 1.2
## enjoyable 13 0.67 0.24 0.754 0.25 1.3
## likable 19 0.60 0.32 0.747 0.25 1.5
## appealing 1 0.58 0.34 0.749 0.25 1.6
## satisfying 28 0.57 0.33 0.724 0.28 1.6
## lovely 20 0.57 0.27 0.639 0.36 1.4
## engaging 12 0.56 0.26 0.615 0.38 1.4
## motivating 21 0.54 0.34 0.684 0.32 1.7
## delightful 10 0.53 0.35 0.687 0.31 1.7
## nice 22 0.53 0.40 0.764 0.24 1.9
## pleasing 24 0.50 0.45 0.791 0.21 2.0
## provoking 27 0.36 -0.07 0.096 0.90 1.1
## organized 23 -0.31 1.07 0.733 0.27 1.2
## clean 6 -0.16 0.94 0.674 0.33 1.1
## balanced 4 -0.06 0.84 0.641 0.36 1.0
## professional 26 -0.08 0.76 0.493 0.51 1.0
## wellDesigned 31 0.20 0.68 0.704 0.30 1.2
## harmonious 16 0.30 0.58 0.695 0.31 1.5
## elegant 11 0.25 0.54 0.564 0.44 1.4
## inviting 18 0.34 0.54 0.688 0.31 1.7
## cluttered 7 -0.06 0.48 0.194 0.81 1.0
## tasteful 30 0.38 0.44 0.591 0.41 1.9
## colorHarmonious 8 0.31 0.37 0.408 0.59 1.9
## sophisticated 29 0.29 0.36 0.371 0.63 1.9
##
## PA1 PA2
## SS loadings 11.11 8.18
## Proportion Var 0.36 0.26
## Cumulative Var 0.36 0.62
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.56
## The degrees of freedom for the model are 404 and the objective function was 3.89
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.97 0.96
## Minimum correlation of possible factor scores 0.94 0.91
##
##
## ## Image 6
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.763 0.24 1
## attractive 3 0.87 0.755 0.24 1
## likable 19 0.84 0.706 0.29 1
## enjoyable 13 0.84 0.702 0.30 1
## nice 22 0.83 0.687 0.31 1
## appealing 1 0.83 0.687 0.31 1
## delightful 10 0.81 0.658 0.34 1
## pretty 25 0.81 0.657 0.34 1
## satisfying 28 0.80 0.645 0.35 1
## inviting 18 0.80 0.639 0.36 1
## tasteful 30 0.78 0.611 0.39 1
## motivating 21 0.78 0.611 0.39 1
## engaging 12 0.78 0.604 0.40 1
## beautiful 5 0.78 0.601 0.40 1
## lovely 20 0.77 0.590 0.41 1
## exciting 14 0.76 0.574 0.43 1
## harmonious 16 0.74 0.554 0.45 1
## wellDesigned 31 0.73 0.534 0.47 1
## fascinating 15 0.72 0.519 0.48 1
## interesting 17 0.71 0.509 0.49 1
## balanced 4 0.69 0.483 0.52 1
## elegant 11 0.68 0.457 0.54 1
## colorHarmonious 8 0.63 0.395 0.60 1
## artistic 2 0.63 0.395 0.61 1
## sophisticated 29 0.62 0.390 0.61 1
## creative 9 0.62 0.386 0.61 1
## clean 6 0.60 0.363 0.64 1
## organized 23 0.59 0.345 0.65 1
## professional 26 0.53 0.282 0.72 1
## provoking 27 0.33 0.108 0.89 1
## cluttered 7 0.18 0.033 0.97 1
##
## PA1
## SS loadings 16.24
## Proportion Var 0.52
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 434 and the objective function was 5.91
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.79 0.02 0.628 0.37 1.0
## fascinating 15 0.76 0.20 0.625 0.38 1.1
## exciting 14 0.76 0.26 0.648 0.35 1.2
## pretty 25 0.75 0.36 0.690 0.31 1.4
## likable 19 0.74 0.42 0.722 0.28 1.6
## creative 9 0.74 0.08 0.548 0.45 1.0
## beautiful 5 0.72 0.33 0.637 0.36 1.4
## lovely 20 0.72 0.32 0.628 0.37 1.4
## attractive 3 0.72 0.48 0.757 0.24 1.7
## pleasing 24 0.71 0.51 0.762 0.24 1.8
## enjoyable 13 0.70 0.46 0.706 0.29 1.7
## engaging 12 0.67 0.40 0.612 0.39 1.6
## appealing 1 0.67 0.49 0.685 0.31 1.8
## interesting 17 0.66 0.31 0.538 0.46 1.4
## delightful 10 0.66 0.47 0.657 0.34 1.8
## nice 22 0.65 0.51 0.685 0.31 1.9
## satisfying 28 0.61 0.52 0.644 0.36 1.9
## tasteful 30 0.58 0.52 0.612 0.39 2.0
## motivating 21 0.58 0.53 0.612 0.39 2.0
## colorHarmonious 8 0.49 0.40 0.394 0.61 1.9
## provoking 27 0.32 0.12 0.119 0.88 1.3
## organized 23 0.13 0.80 0.656 0.34 1.1
## clean 6 0.16 0.78 0.636 0.36 1.1
## wellDesigned 31 0.36 0.73 0.661 0.34 1.5
## balanced 4 0.34 0.69 0.597 0.40 1.5
## professional 26 0.15 0.67 0.474 0.53 1.1
## elegant 11 0.37 0.62 0.528 0.47 1.6
## harmonious 16 0.46 0.62 0.598 0.40 1.8
## inviting 18 0.56 0.58 0.651 0.35 2.0
## sophisticated 29 0.42 0.48 0.403 0.60 2.0
## cluttered 7 0.06 0.22 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 10.74 7.43
## Proportion Var 0.35 0.24
## Cumulative Var 0.35 0.59
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.89
## Minimum correlation of possible factor scores 0.85 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.02 -0.40 0.628 0.37 1.3
## creative 9 0.92 -0.30 0.548 0.45 1.2
## fascinating 15 0.89 -0.16 0.625 0.38 1.1
## exciting 14 0.85 -0.07 0.648 0.35 1.0
## pretty 25 0.79 0.06 0.690 0.31 1.0
## lovely 20 0.77 0.03 0.628 0.37 1.0
## beautiful 5 0.77 0.04 0.637 0.36 1.0
## likable 19 0.74 0.15 0.722 0.28 1.1
## interesting 17 0.70 0.04 0.538 0.46 1.0
## attractive 3 0.69 0.24 0.757 0.24 1.2
## enjoyable 13 0.67 0.22 0.706 0.29 1.2
## engaging 12 0.66 0.16 0.612 0.39 1.1
## pleasing 24 0.65 0.29 0.762 0.24 1.4
## appealing 1 0.61 0.27 0.685 0.31 1.4
## delightful 10 0.61 0.25 0.657 0.34 1.3
## nice 22 0.58 0.31 0.685 0.31 1.5
## satisfying 28 0.52 0.34 0.644 0.36 1.7
## tasteful 30 0.48 0.37 0.612 0.39 1.9
## motivating 21 0.48 0.37 0.612 0.39 1.9
## colorHarmonious 8 0.43 0.25 0.394 0.61 1.6
## provoking 27 0.36 -0.02 0.119 0.88 1.0
## organized 23 -0.26 0.97 0.656 0.34 1.1
## clean 6 -0.21 0.93 0.636 0.36 1.1
## professional 26 -0.16 0.79 0.474 0.53 1.1
## wellDesigned 31 0.08 0.75 0.661 0.34 1.0
## balanced 4 0.08 0.72 0.597 0.40 1.0
## elegant 11 0.15 0.61 0.528 0.47 1.1
## harmonious 16 0.26 0.57 0.598 0.40 1.4
## inviting 18 0.41 0.46 0.651 0.35 2.0
## sophisticated 29 0.29 0.39 0.403 0.60 1.9
## cluttered 7 -0.04 0.25 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 11.49 6.67
## Proportion Var 0.37 0.22
## Cumulative Var 0.37 0.59
## Proportion Explained 0.63 0.37
## Cumulative Proportion 0.63 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.763 0.24 1
## attractive 3 0.87 0.755 0.24 1
## likable 19 0.84 0.706 0.29 1
## enjoyable 13 0.84 0.702 0.30 1
## nice 22 0.83 0.687 0.31 1
## appealing 1 0.83 0.687 0.31 1
## delightful 10 0.81 0.658 0.34 1
## pretty 25 0.81 0.657 0.34 1
## satisfying 28 0.80 0.645 0.35 1
## inviting 18 0.80 0.639 0.36 1
## tasteful 30 0.78 0.611 0.39 1
## motivating 21 0.78 0.611 0.39 1
## engaging 12 0.78 0.604 0.40 1
## beautiful 5 0.78 0.601 0.40 1
## lovely 20 0.77 0.590 0.41 1
## exciting 14 0.76 0.574 0.43 1
## harmonious 16 0.74 0.554 0.45 1
## wellDesigned 31 0.73 0.534 0.47 1
## fascinating 15 0.72 0.519 0.48 1
## interesting 17 0.71 0.509 0.49 1
## balanced 4 0.69 0.483 0.52 1
## elegant 11 0.68 0.457 0.54 1
## colorHarmonious 8 0.63 0.395 0.60 1
## artistic 2 0.63 0.395 0.61 1
## sophisticated 29 0.62 0.390 0.61 1
## creative 9 0.62 0.386 0.61 1
## clean 6 0.60 0.363 0.64 1
## organized 23 0.59 0.345 0.65 1
## professional 26 0.53 0.282 0.72 1
## provoking 27 0.33 0.108 0.89 1
## cluttered 7 0.18 0.033 0.97 1
##
## PA1
## SS loadings 16.24
## Proportion Var 0.52
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 434 and the objective function was 5.91
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.79 0.02 0.628 0.37 1.0
## fascinating 15 0.76 0.20 0.625 0.38 1.1
## exciting 14 0.76 0.26 0.648 0.35 1.2
## pretty 25 0.75 0.36 0.690 0.31 1.4
## likable 19 0.74 0.42 0.722 0.28 1.6
## creative 9 0.74 0.08 0.548 0.45 1.0
## beautiful 5 0.72 0.33 0.637 0.36 1.4
## lovely 20 0.72 0.32 0.628 0.37 1.4
## attractive 3 0.72 0.48 0.757 0.24 1.7
## pleasing 24 0.71 0.51 0.762 0.24 1.8
## enjoyable 13 0.70 0.46 0.706 0.29 1.7
## engaging 12 0.67 0.40 0.612 0.39 1.6
## appealing 1 0.67 0.49 0.685 0.31 1.8
## interesting 17 0.66 0.31 0.538 0.46 1.4
## delightful 10 0.66 0.47 0.657 0.34 1.8
## nice 22 0.65 0.51 0.685 0.31 1.9
## satisfying 28 0.61 0.52 0.644 0.36 1.9
## tasteful 30 0.58 0.52 0.612 0.39 2.0
## motivating 21 0.58 0.53 0.612 0.39 2.0
## colorHarmonious 8 0.49 0.40 0.394 0.61 1.9
## provoking 27 0.32 0.12 0.119 0.88 1.3
## organized 23 0.13 0.80 0.656 0.34 1.1
## clean 6 0.16 0.78 0.636 0.36 1.1
## wellDesigned 31 0.36 0.73 0.661 0.34 1.5
## balanced 4 0.34 0.69 0.597 0.40 1.5
## professional 26 0.15 0.67 0.474 0.53 1.1
## elegant 11 0.37 0.62 0.528 0.47 1.6
## harmonious 16 0.46 0.62 0.598 0.40 1.8
## inviting 18 0.56 0.58 0.651 0.35 2.0
## sophisticated 29 0.42 0.48 0.403 0.60 2.0
## cluttered 7 0.06 0.22 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 10.74 7.43
## Proportion Var 0.35 0.24
## Cumulative Var 0.35 0.59
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.89
## Minimum correlation of possible factor scores 0.85 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.02 -0.40 0.628 0.37 1.3
## creative 9 0.92 -0.30 0.548 0.45 1.2
## fascinating 15 0.89 -0.16 0.625 0.38 1.1
## exciting 14 0.85 -0.07 0.648 0.35 1.0
## pretty 25 0.79 0.06 0.690 0.31 1.0
## lovely 20 0.77 0.03 0.628 0.37 1.0
## beautiful 5 0.77 0.04 0.637 0.36 1.0
## likable 19 0.74 0.15 0.722 0.28 1.1
## interesting 17 0.70 0.04 0.538 0.46 1.0
## attractive 3 0.69 0.24 0.757 0.24 1.2
## enjoyable 13 0.67 0.22 0.706 0.29 1.2
## engaging 12 0.66 0.16 0.612 0.39 1.1
## pleasing 24 0.65 0.29 0.762 0.24 1.4
## appealing 1 0.61 0.27 0.685 0.31 1.4
## delightful 10 0.61 0.25 0.657 0.34 1.3
## nice 22 0.58 0.31 0.685 0.31 1.5
## satisfying 28 0.52 0.34 0.644 0.36 1.7
## tasteful 30 0.48 0.37 0.612 0.39 1.9
## motivating 21 0.48 0.37 0.612 0.39 1.9
## colorHarmonious 8 0.43 0.25 0.394 0.61 1.6
## provoking 27 0.36 -0.02 0.119 0.88 1.0
## organized 23 -0.26 0.97 0.656 0.34 1.1
## clean 6 -0.21 0.93 0.636 0.36 1.1
## professional 26 -0.16 0.79 0.474 0.53 1.1
## wellDesigned 31 0.08 0.75 0.661 0.34 1.0
## balanced 4 0.08 0.72 0.597 0.40 1.0
## elegant 11 0.15 0.61 0.528 0.47 1.1
## harmonious 16 0.26 0.57 0.598 0.40 1.4
## inviting 18 0.41 0.46 0.651 0.35 2.0
## sophisticated 29 0.29 0.39 0.403 0.60 1.9
## cluttered 7 -0.04 0.25 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 11.49 6.67
## Proportion Var 0.37 0.22
## Cumulative Var 0.37 0.59
## Proportion Explained 0.63 0.37
## Cumulative Proportion 0.63 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.763 0.24 1
## attractive 3 0.87 0.755 0.24 1
## likable 19 0.84 0.706 0.29 1
## enjoyable 13 0.84 0.702 0.30 1
## nice 22 0.83 0.687 0.31 1
## appealing 1 0.83 0.687 0.31 1
## delightful 10 0.81 0.658 0.34 1
## pretty 25 0.81 0.657 0.34 1
## satisfying 28 0.80 0.645 0.35 1
## inviting 18 0.80 0.639 0.36 1
## tasteful 30 0.78 0.611 0.39 1
## motivating 21 0.78 0.611 0.39 1
## engaging 12 0.78 0.604 0.40 1
## beautiful 5 0.78 0.601 0.40 1
## lovely 20 0.77 0.590 0.41 1
## exciting 14 0.76 0.574 0.43 1
## harmonious 16 0.74 0.554 0.45 1
## wellDesigned 31 0.73 0.534 0.47 1
## fascinating 15 0.72 0.519 0.48 1
## interesting 17 0.71 0.509 0.49 1
## balanced 4 0.69 0.483 0.52 1
## elegant 11 0.68 0.457 0.54 1
## colorHarmonious 8 0.63 0.395 0.60 1
## artistic 2 0.63 0.395 0.61 1
## sophisticated 29 0.62 0.390 0.61 1
## creative 9 0.62 0.386 0.61 1
## clean 6 0.60 0.363 0.64 1
## organized 23 0.59 0.345 0.65 1
## professional 26 0.53 0.282 0.72 1
## provoking 27 0.33 0.108 0.89 1
## cluttered 7 0.18 0.033 0.97 1
##
## PA1
## SS loadings 16.24
## Proportion Var 0.52
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 434 and the objective function was 5.91
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.79 0.02 0.628 0.37 1.0
## fascinating 15 0.76 0.20 0.625 0.38 1.1
## exciting 14 0.76 0.26 0.648 0.35 1.2
## pretty 25 0.75 0.36 0.690 0.31 1.4
## likable 19 0.74 0.42 0.722 0.28 1.6
## creative 9 0.74 0.08 0.548 0.45 1.0
## beautiful 5 0.72 0.33 0.637 0.36 1.4
## lovely 20 0.72 0.32 0.628 0.37 1.4
## attractive 3 0.72 0.48 0.757 0.24 1.7
## pleasing 24 0.71 0.51 0.762 0.24 1.8
## enjoyable 13 0.70 0.46 0.706 0.29 1.7
## engaging 12 0.67 0.40 0.612 0.39 1.6
## appealing 1 0.67 0.49 0.685 0.31 1.8
## interesting 17 0.66 0.31 0.538 0.46 1.4
## delightful 10 0.66 0.47 0.657 0.34 1.8
## nice 22 0.65 0.51 0.685 0.31 1.9
## satisfying 28 0.61 0.52 0.644 0.36 1.9
## tasteful 30 0.58 0.52 0.612 0.39 2.0
## motivating 21 0.58 0.53 0.612 0.39 2.0
## colorHarmonious 8 0.49 0.40 0.394 0.61 1.9
## provoking 27 0.32 0.12 0.119 0.88 1.3
## organized 23 0.13 0.80 0.656 0.34 1.1
## clean 6 0.16 0.78 0.636 0.36 1.1
## wellDesigned 31 0.36 0.73 0.661 0.34 1.5
## balanced 4 0.34 0.69 0.597 0.40 1.5
## professional 26 0.15 0.67 0.474 0.53 1.1
## elegant 11 0.37 0.62 0.528 0.47 1.6
## harmonious 16 0.46 0.62 0.598 0.40 1.8
## inviting 18 0.56 0.58 0.651 0.35 2.0
## sophisticated 29 0.42 0.48 0.403 0.60 2.0
## cluttered 7 0.06 0.22 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 10.74 7.43
## Proportion Var 0.35 0.24
## Cumulative Var 0.35 0.59
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.89
## Minimum correlation of possible factor scores 0.85 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.02 -0.40 0.628 0.37 1.3
## creative 9 0.92 -0.30 0.548 0.45 1.2
## fascinating 15 0.89 -0.16 0.625 0.38 1.1
## exciting 14 0.85 -0.07 0.648 0.35 1.0
## pretty 25 0.79 0.06 0.690 0.31 1.0
## lovely 20 0.77 0.03 0.628 0.37 1.0
## beautiful 5 0.77 0.04 0.637 0.36 1.0
## likable 19 0.74 0.15 0.722 0.28 1.1
## interesting 17 0.70 0.04 0.538 0.46 1.0
## attractive 3 0.69 0.24 0.757 0.24 1.2
## enjoyable 13 0.67 0.22 0.706 0.29 1.2
## engaging 12 0.66 0.16 0.612 0.39 1.1
## pleasing 24 0.65 0.29 0.762 0.24 1.4
## appealing 1 0.61 0.27 0.685 0.31 1.4
## delightful 10 0.61 0.25 0.657 0.34 1.3
## nice 22 0.58 0.31 0.685 0.31 1.5
## satisfying 28 0.52 0.34 0.644 0.36 1.7
## tasteful 30 0.48 0.37 0.612 0.39 1.9
## motivating 21 0.48 0.37 0.612 0.39 1.9
## colorHarmonious 8 0.43 0.25 0.394 0.61 1.6
## provoking 27 0.36 -0.02 0.119 0.88 1.0
## organized 23 -0.26 0.97 0.656 0.34 1.1
## clean 6 -0.21 0.93 0.636 0.36 1.1
## professional 26 -0.16 0.79 0.474 0.53 1.1
## wellDesigned 31 0.08 0.75 0.661 0.34 1.0
## balanced 4 0.08 0.72 0.597 0.40 1.0
## elegant 11 0.15 0.61 0.528 0.47 1.1
## harmonious 16 0.26 0.57 0.598 0.40 1.4
## inviting 18 0.41 0.46 0.651 0.35 2.0
## sophisticated 29 0.29 0.39 0.403 0.60 1.9
## cluttered 7 -0.04 0.25 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 11.49 6.67
## Proportion Var 0.37 0.22
## Cumulative Var 0.37 0.59
## Proportion Explained 0.63 0.37
## Cumulative Proportion 0.63 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.763 0.24 1
## attractive 3 0.87 0.755 0.24 1
## likable 19 0.84 0.706 0.29 1
## enjoyable 13 0.84 0.702 0.30 1
## nice 22 0.83 0.687 0.31 1
## appealing 1 0.83 0.687 0.31 1
## delightful 10 0.81 0.658 0.34 1
## pretty 25 0.81 0.657 0.34 1
## satisfying 28 0.80 0.645 0.35 1
## inviting 18 0.80 0.639 0.36 1
## tasteful 30 0.78 0.611 0.39 1
## motivating 21 0.78 0.611 0.39 1
## engaging 12 0.78 0.604 0.40 1
## beautiful 5 0.78 0.601 0.40 1
## lovely 20 0.77 0.590 0.41 1
## exciting 14 0.76 0.574 0.43 1
## harmonious 16 0.74 0.554 0.45 1
## wellDesigned 31 0.73 0.534 0.47 1
## fascinating 15 0.72 0.519 0.48 1
## interesting 17 0.71 0.509 0.49 1
## balanced 4 0.69 0.483 0.52 1
## elegant 11 0.68 0.457 0.54 1
## colorHarmonious 8 0.63 0.395 0.60 1
## artistic 2 0.63 0.395 0.61 1
## sophisticated 29 0.62 0.390 0.61 1
## creative 9 0.62 0.386 0.61 1
## clean 6 0.60 0.363 0.64 1
## organized 23 0.59 0.345 0.65 1
## professional 26 0.53 0.282 0.72 1
## provoking 27 0.33 0.108 0.89 1
## cluttered 7 0.18 0.033 0.97 1
##
## PA1
## SS loadings 16.24
## Proportion Var 0.52
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 434 and the objective function was 5.91
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.79 0.02 0.628 0.37 1.0
## fascinating 15 0.76 0.20 0.625 0.38 1.1
## exciting 14 0.76 0.26 0.648 0.35 1.2
## pretty 25 0.75 0.36 0.690 0.31 1.4
## likable 19 0.74 0.42 0.722 0.28 1.6
## creative 9 0.74 0.08 0.548 0.45 1.0
## beautiful 5 0.72 0.33 0.637 0.36 1.4
## lovely 20 0.72 0.32 0.628 0.37 1.4
## attractive 3 0.72 0.48 0.757 0.24 1.7
## pleasing 24 0.71 0.51 0.762 0.24 1.8
## enjoyable 13 0.70 0.46 0.706 0.29 1.7
## engaging 12 0.67 0.40 0.612 0.39 1.6
## appealing 1 0.67 0.49 0.685 0.31 1.8
## interesting 17 0.66 0.31 0.538 0.46 1.4
## delightful 10 0.66 0.47 0.657 0.34 1.8
## nice 22 0.65 0.51 0.685 0.31 1.9
## satisfying 28 0.61 0.52 0.644 0.36 1.9
## tasteful 30 0.58 0.52 0.612 0.39 2.0
## motivating 21 0.58 0.53 0.612 0.39 2.0
## colorHarmonious 8 0.49 0.40 0.394 0.61 1.9
## provoking 27 0.32 0.12 0.119 0.88 1.3
## organized 23 0.13 0.80 0.656 0.34 1.1
## clean 6 0.16 0.78 0.636 0.36 1.1
## wellDesigned 31 0.36 0.73 0.661 0.34 1.5
## balanced 4 0.34 0.69 0.597 0.40 1.5
## professional 26 0.15 0.67 0.474 0.53 1.1
## elegant 11 0.37 0.62 0.528 0.47 1.6
## harmonious 16 0.46 0.62 0.598 0.40 1.8
## inviting 18 0.56 0.58 0.651 0.35 2.0
## sophisticated 29 0.42 0.48 0.403 0.60 2.0
## cluttered 7 0.06 0.22 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 10.74 7.43
## Proportion Var 0.35 0.24
## Cumulative Var 0.35 0.59
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.89
## Minimum correlation of possible factor scores 0.85 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.02 -0.40 0.628 0.37 1.3
## creative 9 0.92 -0.30 0.548 0.45 1.2
## fascinating 15 0.89 -0.16 0.625 0.38 1.1
## exciting 14 0.85 -0.07 0.648 0.35 1.0
## pretty 25 0.79 0.06 0.690 0.31 1.0
## lovely 20 0.77 0.03 0.628 0.37 1.0
## beautiful 5 0.77 0.04 0.637 0.36 1.0
## likable 19 0.74 0.15 0.722 0.28 1.1
## interesting 17 0.70 0.04 0.538 0.46 1.0
## attractive 3 0.69 0.24 0.757 0.24 1.2
## enjoyable 13 0.67 0.22 0.706 0.29 1.2
## engaging 12 0.66 0.16 0.612 0.39 1.1
## pleasing 24 0.65 0.29 0.762 0.24 1.4
## appealing 1 0.61 0.27 0.685 0.31 1.4
## delightful 10 0.61 0.25 0.657 0.34 1.3
## nice 22 0.58 0.31 0.685 0.31 1.5
## satisfying 28 0.52 0.34 0.644 0.36 1.7
## tasteful 30 0.48 0.37 0.612 0.39 1.9
## motivating 21 0.48 0.37 0.612 0.39 1.9
## colorHarmonious 8 0.43 0.25 0.394 0.61 1.6
## provoking 27 0.36 -0.02 0.119 0.88 1.0
## organized 23 -0.26 0.97 0.656 0.34 1.1
## clean 6 -0.21 0.93 0.636 0.36 1.1
## professional 26 -0.16 0.79 0.474 0.53 1.1
## wellDesigned 31 0.08 0.75 0.661 0.34 1.0
## balanced 4 0.08 0.72 0.597 0.40 1.0
## elegant 11 0.15 0.61 0.528 0.47 1.1
## harmonious 16 0.26 0.57 0.598 0.40 1.4
## inviting 18 0.41 0.46 0.651 0.35 2.0
## sophisticated 29 0.29 0.39 0.403 0.60 1.9
## cluttered 7 -0.04 0.25 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 11.49 6.67
## Proportion Var 0.37 0.22
## Cumulative Var 0.37 0.59
## Proportion Explained 0.63 0.37
## Cumulative Proportion 0.63 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.763 0.24 1
## attractive 3 0.87 0.755 0.24 1
## likable 19 0.84 0.706 0.29 1
## enjoyable 13 0.84 0.702 0.30 1
## nice 22 0.83 0.687 0.31 1
## appealing 1 0.83 0.687 0.31 1
## delightful 10 0.81 0.658 0.34 1
## pretty 25 0.81 0.657 0.34 1
## satisfying 28 0.80 0.645 0.35 1
## inviting 18 0.80 0.639 0.36 1
## tasteful 30 0.78 0.611 0.39 1
## motivating 21 0.78 0.611 0.39 1
## engaging 12 0.78 0.604 0.40 1
## beautiful 5 0.78 0.601 0.40 1
## lovely 20 0.77 0.590 0.41 1
## exciting 14 0.76 0.574 0.43 1
## harmonious 16 0.74 0.554 0.45 1
## wellDesigned 31 0.73 0.534 0.47 1
## fascinating 15 0.72 0.519 0.48 1
## interesting 17 0.71 0.509 0.49 1
## balanced 4 0.69 0.483 0.52 1
## elegant 11 0.68 0.457 0.54 1
## colorHarmonious 8 0.63 0.395 0.60 1
## artistic 2 0.63 0.395 0.61 1
## sophisticated 29 0.62 0.390 0.61 1
## creative 9 0.62 0.386 0.61 1
## clean 6 0.60 0.363 0.64 1
## organized 23 0.59 0.345 0.65 1
## professional 26 0.53 0.282 0.72 1
## provoking 27 0.33 0.108 0.89 1
## cluttered 7 0.18 0.033 0.97 1
##
## PA1
## SS loadings 16.24
## Proportion Var 0.52
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 434 and the objective function was 5.91
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.79 0.02 0.628 0.37 1.0
## fascinating 15 0.76 0.20 0.625 0.38 1.1
## exciting 14 0.76 0.26 0.648 0.35 1.2
## pretty 25 0.75 0.36 0.690 0.31 1.4
## likable 19 0.74 0.42 0.722 0.28 1.6
## creative 9 0.74 0.08 0.548 0.45 1.0
## beautiful 5 0.72 0.33 0.637 0.36 1.4
## lovely 20 0.72 0.32 0.628 0.37 1.4
## attractive 3 0.72 0.48 0.757 0.24 1.7
## pleasing 24 0.71 0.51 0.762 0.24 1.8
## enjoyable 13 0.70 0.46 0.706 0.29 1.7
## engaging 12 0.67 0.40 0.612 0.39 1.6
## appealing 1 0.67 0.49 0.685 0.31 1.8
## interesting 17 0.66 0.31 0.538 0.46 1.4
## delightful 10 0.66 0.47 0.657 0.34 1.8
## nice 22 0.65 0.51 0.685 0.31 1.9
## satisfying 28 0.61 0.52 0.644 0.36 1.9
## tasteful 30 0.58 0.52 0.612 0.39 2.0
## motivating 21 0.58 0.53 0.612 0.39 2.0
## colorHarmonious 8 0.49 0.40 0.394 0.61 1.9
## provoking 27 0.32 0.12 0.119 0.88 1.3
## organized 23 0.13 0.80 0.656 0.34 1.1
## clean 6 0.16 0.78 0.636 0.36 1.1
## wellDesigned 31 0.36 0.73 0.661 0.34 1.5
## balanced 4 0.34 0.69 0.597 0.40 1.5
## professional 26 0.15 0.67 0.474 0.53 1.1
## elegant 11 0.37 0.62 0.528 0.47 1.6
## harmonious 16 0.46 0.62 0.598 0.40 1.8
## inviting 18 0.56 0.58 0.651 0.35 2.0
## sophisticated 29 0.42 0.48 0.403 0.60 2.0
## cluttered 7 0.06 0.22 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 10.74 7.43
## Proportion Var 0.35 0.24
## Cumulative Var 0.35 0.59
## Proportion Explained 0.59 0.41
## Cumulative Proportion 0.59 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.89
## Minimum correlation of possible factor scores 0.85 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.02 -0.40 0.628 0.37 1.3
## creative 9 0.92 -0.30 0.548 0.45 1.2
## fascinating 15 0.89 -0.16 0.625 0.38 1.1
## exciting 14 0.85 -0.07 0.648 0.35 1.0
## pretty 25 0.79 0.06 0.690 0.31 1.0
## lovely 20 0.77 0.03 0.628 0.37 1.0
## beautiful 5 0.77 0.04 0.637 0.36 1.0
## likable 19 0.74 0.15 0.722 0.28 1.1
## interesting 17 0.70 0.04 0.538 0.46 1.0
## attractive 3 0.69 0.24 0.757 0.24 1.2
## enjoyable 13 0.67 0.22 0.706 0.29 1.2
## engaging 12 0.66 0.16 0.612 0.39 1.1
## pleasing 24 0.65 0.29 0.762 0.24 1.4
## appealing 1 0.61 0.27 0.685 0.31 1.4
## delightful 10 0.61 0.25 0.657 0.34 1.3
## nice 22 0.58 0.31 0.685 0.31 1.5
## satisfying 28 0.52 0.34 0.644 0.36 1.7
## tasteful 30 0.48 0.37 0.612 0.39 1.9
## motivating 21 0.48 0.37 0.612 0.39 1.9
## colorHarmonious 8 0.43 0.25 0.394 0.61 1.6
## provoking 27 0.36 -0.02 0.119 0.88 1.0
## organized 23 -0.26 0.97 0.656 0.34 1.1
## clean 6 -0.21 0.93 0.636 0.36 1.1
## professional 26 -0.16 0.79 0.474 0.53 1.1
## wellDesigned 31 0.08 0.75 0.661 0.34 1.0
## balanced 4 0.08 0.72 0.597 0.40 1.0
## elegant 11 0.15 0.61 0.528 0.47 1.1
## harmonious 16 0.26 0.57 0.598 0.40 1.4
## inviting 18 0.41 0.46 0.651 0.35 2.0
## sophisticated 29 0.29 0.39 0.403 0.60 1.9
## cluttered 7 -0.04 0.25 0.051 0.95 1.1
##
## PA1 PA2
## SS loadings 11.49 6.67
## Proportion Var 0.37 0.22
## Cumulative Var 0.37 0.59
## Proportion Explained 0.63 0.37
## Cumulative Proportion 0.63 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.12
## The degrees of freedom for the model are 404 and the objective function was 3.73
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Image 7
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## satisfying 28 0.90 0.813 0.19 1
## likable 19 0.90 0.807 0.19 1
## pleasing 24 0.90 0.803 0.20 1
## attractive 3 0.89 0.795 0.20 1
## delightful 10 0.89 0.787 0.21 1
## enjoyable 13 0.88 0.781 0.22 1
## pretty 25 0.88 0.773 0.23 1
## appealing 1 0.88 0.767 0.23 1
## beautiful 5 0.87 0.761 0.24 1
## nice 22 0.87 0.760 0.24 1
## motivating 21 0.84 0.706 0.29 1
## inviting 18 0.84 0.703 0.30 1
## lovely 20 0.83 0.693 0.31 1
## elegant 11 0.83 0.691 0.31 1
## engaging 12 0.82 0.674 0.33 1
## exciting 14 0.81 0.657 0.34 1
## fascinating 15 0.80 0.647 0.35 1
## tasteful 30 0.80 0.642 0.36 1
## harmonious 16 0.74 0.550 0.45 1
## sophisticated 29 0.73 0.529 0.47 1
## interesting 17 0.73 0.527 0.47 1
## artistic 2 0.69 0.471 0.53 1
## wellDesigned 31 0.69 0.471 0.53 1
## clean 6 0.66 0.432 0.57 1
## creative 9 0.66 0.430 0.57 1
## professional 26 0.60 0.355 0.64 1
## balanced 4 0.59 0.344 0.66 1
## organized 23 0.55 0.304 0.70 1
## colorHarmonious 8 0.48 0.227 0.77 1
## cluttered 7 0.27 0.072 0.93 1
## provoking 27 0.19 0.037 0.96 1
##
## PA1
## SS loadings 18.01
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 434 and the objective function was 6.4
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.97
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.78 0.16 0.63 0.37 1.1
## elegant 11 0.72 0.46 0.72 0.28 1.7
## organized 23 0.72 0.06 0.52 0.48 1.0
## satisfying 28 0.69 0.59 0.82 0.18 2.0
## pleasing 24 0.67 0.60 0.80 0.20 2.0
## professional 26 0.64 0.20 0.45 0.55 1.2
## motivating 21 0.63 0.55 0.71 0.29 2.0
## delightful 10 0.63 0.63 0.79 0.21 2.0
## wellDesigned 31 0.63 0.34 0.51 0.49 1.5
## harmonious 16 0.62 0.43 0.57 0.43 1.8
## nice 22 0.62 0.61 0.76 0.24 2.0
## tasteful 30 0.60 0.53 0.64 0.36 2.0
## lovely 20 0.60 0.58 0.69 0.31 2.0
## inviting 18 0.60 0.59 0.70 0.30 2.0
## balanced 4 0.59 0.23 0.41 0.59 1.3
## sophisticated 29 0.58 0.45 0.54 0.46 1.9
## colorHarmonious 8 0.38 0.30 0.23 0.77 1.9
## cluttered 7 0.34 0.04 0.12 0.88 1.0
## fascinating 15 0.36 0.79 0.76 0.24 1.4
## interesting 17 0.29 0.75 0.64 0.36 1.3
## creative 9 0.20 0.74 0.59 0.41 1.1
## artistic 2 0.25 0.74 0.60 0.40 1.2
## exciting 14 0.47 0.68 0.68 0.32 1.8
## beautiful 5 0.57 0.67 0.77 0.23 1.9
## engaging 12 0.50 0.66 0.69 0.31 1.9
## pretty 25 0.59 0.65 0.77 0.23 2.0
## enjoyable 13 0.60 0.65 0.78 0.22 2.0
## likable 19 0.62 0.65 0.81 0.19 2.0
## attractive 3 0.62 0.64 0.79 0.21 2.0
## appealing 1 0.62 0.62 0.77 0.23 2.0
## provoking 27 -0.11 0.39 0.16 0.84 1.2
##
## PA1 PA2
## SS loadings 9.90 9.50
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.94
## Multiple R square of scores with factors 0.88 0.88
## Minimum correlation of possible factor scores 0.75 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.92 -0.21 0.63 0.37 1.1
## organized 23 0.89 -0.29 0.52 0.48 1.2
## professional 26 0.73 -0.08 0.45 0.55 1.0
## elegant 11 0.69 0.21 0.72 0.28 1.2
## balanced 4 0.65 -0.01 0.41 0.59 1.0
## wellDesigned 31 0.63 0.11 0.51 0.49 1.1
## satisfying 28 0.58 0.40 0.82 0.18 1.8
## harmonious 16 0.58 0.22 0.57 0.43 1.3
## pleasing 24 0.55 0.42 0.80 0.20 1.9
## motivating 21 0.52 0.39 0.71 0.29 1.8
## sophisticated 29 0.51 0.27 0.54 0.46 1.5
## tasteful 30 0.50 0.37 0.64 0.36 1.8
## nice 22 0.47 0.47 0.76 0.24 2.0
## lovely 20 0.46 0.44 0.69 0.31 2.0
## inviting 18 0.46 0.45 0.70 0.30 2.0
## cluttered 7 0.42 -0.13 0.12 0.88 1.2
## colorHarmonious 8 0.33 0.18 0.23 0.77 1.6
## creative 9 -0.14 0.86 0.59 0.41 1.1
## fascinating 15 0.04 0.84 0.76 0.24 1.0
## artistic 2 -0.07 0.83 0.60 0.40 1.0
## interesting 17 -0.02 0.82 0.64 0.36 1.0
## exciting 14 0.25 0.63 0.68 0.32 1.3
## engaging 12 0.29 0.60 0.69 0.31 1.4
## beautiful 5 0.38 0.57 0.77 0.23 1.7
## provoking 27 -0.35 0.56 0.16 0.84 1.7
## pretty 25 0.42 0.54 0.77 0.23 1.9
## enjoyable 13 0.43 0.53 0.78 0.22 1.9
## likable 19 0.46 0.51 0.81 0.19 2.0
## attractive 3 0.46 0.51 0.79 0.21 2.0
## delightful 10 0.48 0.48 0.79 0.21 2.0
## appealing 1 0.47 0.48 0.77 0.23 2.0
##
## PA1 PA2
## SS loadings 9.93 9.48
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.0 0.7
## PA2 0.7 1.0
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.95 0.95
## Minimum correlation of possible factor scores 0.90 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## satisfying 28 0.90 0.813 0.19 1
## likable 19 0.90 0.807 0.19 1
## pleasing 24 0.90 0.803 0.20 1
## attractive 3 0.89 0.795 0.20 1
## delightful 10 0.89 0.787 0.21 1
## enjoyable 13 0.88 0.781 0.22 1
## pretty 25 0.88 0.773 0.23 1
## appealing 1 0.88 0.767 0.23 1
## beautiful 5 0.87 0.761 0.24 1
## nice 22 0.87 0.760 0.24 1
## motivating 21 0.84 0.706 0.29 1
## inviting 18 0.84 0.703 0.30 1
## lovely 20 0.83 0.693 0.31 1
## elegant 11 0.83 0.691 0.31 1
## engaging 12 0.82 0.674 0.33 1
## exciting 14 0.81 0.657 0.34 1
## fascinating 15 0.80 0.647 0.35 1
## tasteful 30 0.80 0.642 0.36 1
## harmonious 16 0.74 0.550 0.45 1
## sophisticated 29 0.73 0.529 0.47 1
## interesting 17 0.73 0.527 0.47 1
## artistic 2 0.69 0.471 0.53 1
## wellDesigned 31 0.69 0.471 0.53 1
## clean 6 0.66 0.432 0.57 1
## creative 9 0.66 0.430 0.57 1
## professional 26 0.60 0.355 0.64 1
## balanced 4 0.59 0.344 0.66 1
## organized 23 0.55 0.304 0.70 1
## colorHarmonious 8 0.48 0.227 0.77 1
## cluttered 7 0.27 0.072 0.93 1
## provoking 27 0.19 0.037 0.96 1
##
## PA1
## SS loadings 18.01
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 434 and the objective function was 6.4
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.97
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.78 0.16 0.63 0.37 1.1
## elegant 11 0.72 0.46 0.72 0.28 1.7
## organized 23 0.72 0.06 0.52 0.48 1.0
## satisfying 28 0.69 0.59 0.82 0.18 2.0
## pleasing 24 0.67 0.60 0.80 0.20 2.0
## professional 26 0.64 0.20 0.45 0.55 1.2
## motivating 21 0.63 0.55 0.71 0.29 2.0
## delightful 10 0.63 0.63 0.79 0.21 2.0
## wellDesigned 31 0.63 0.34 0.51 0.49 1.5
## harmonious 16 0.62 0.43 0.57 0.43 1.8
## nice 22 0.62 0.61 0.76 0.24 2.0
## tasteful 30 0.60 0.53 0.64 0.36 2.0
## lovely 20 0.60 0.58 0.69 0.31 2.0
## inviting 18 0.60 0.59 0.70 0.30 2.0
## balanced 4 0.59 0.23 0.41 0.59 1.3
## sophisticated 29 0.58 0.45 0.54 0.46 1.9
## colorHarmonious 8 0.38 0.30 0.23 0.77 1.9
## cluttered 7 0.34 0.04 0.12 0.88 1.0
## fascinating 15 0.36 0.79 0.76 0.24 1.4
## interesting 17 0.29 0.75 0.64 0.36 1.3
## creative 9 0.20 0.74 0.59 0.41 1.1
## artistic 2 0.25 0.74 0.60 0.40 1.2
## exciting 14 0.47 0.68 0.68 0.32 1.8
## beautiful 5 0.57 0.67 0.77 0.23 1.9
## engaging 12 0.50 0.66 0.69 0.31 1.9
## pretty 25 0.59 0.65 0.77 0.23 2.0
## enjoyable 13 0.60 0.65 0.78 0.22 2.0
## likable 19 0.62 0.65 0.81 0.19 2.0
## attractive 3 0.62 0.64 0.79 0.21 2.0
## appealing 1 0.62 0.62 0.77 0.23 2.0
## provoking 27 -0.11 0.39 0.16 0.84 1.2
##
## PA1 PA2
## SS loadings 9.90 9.50
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.94
## Multiple R square of scores with factors 0.88 0.88
## Minimum correlation of possible factor scores 0.75 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.92 -0.21 0.63 0.37 1.1
## organized 23 0.89 -0.29 0.52 0.48 1.2
## professional 26 0.73 -0.08 0.45 0.55 1.0
## elegant 11 0.69 0.21 0.72 0.28 1.2
## balanced 4 0.65 -0.01 0.41 0.59 1.0
## wellDesigned 31 0.63 0.11 0.51 0.49 1.1
## satisfying 28 0.58 0.40 0.82 0.18 1.8
## harmonious 16 0.58 0.22 0.57 0.43 1.3
## pleasing 24 0.55 0.42 0.80 0.20 1.9
## motivating 21 0.52 0.39 0.71 0.29 1.8
## sophisticated 29 0.51 0.27 0.54 0.46 1.5
## tasteful 30 0.50 0.37 0.64 0.36 1.8
## nice 22 0.47 0.47 0.76 0.24 2.0
## lovely 20 0.46 0.44 0.69 0.31 2.0
## inviting 18 0.46 0.45 0.70 0.30 2.0
## cluttered 7 0.42 -0.13 0.12 0.88 1.2
## colorHarmonious 8 0.33 0.18 0.23 0.77 1.6
## creative 9 -0.14 0.86 0.59 0.41 1.1
## fascinating 15 0.04 0.84 0.76 0.24 1.0
## artistic 2 -0.07 0.83 0.60 0.40 1.0
## interesting 17 -0.02 0.82 0.64 0.36 1.0
## exciting 14 0.25 0.63 0.68 0.32 1.3
## engaging 12 0.29 0.60 0.69 0.31 1.4
## beautiful 5 0.38 0.57 0.77 0.23 1.7
## provoking 27 -0.35 0.56 0.16 0.84 1.7
## pretty 25 0.42 0.54 0.77 0.23 1.9
## enjoyable 13 0.43 0.53 0.78 0.22 1.9
## likable 19 0.46 0.51 0.81 0.19 2.0
## attractive 3 0.46 0.51 0.79 0.21 2.0
## delightful 10 0.48 0.48 0.79 0.21 2.0
## appealing 1 0.47 0.48 0.77 0.23 2.0
##
## PA1 PA2
## SS loadings 9.93 9.48
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.0 0.7
## PA2 0.7 1.0
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.95 0.95
## Minimum correlation of possible factor scores 0.90 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## satisfying 28 0.90 0.813 0.19 1
## likable 19 0.90 0.807 0.19 1
## pleasing 24 0.90 0.803 0.20 1
## attractive 3 0.89 0.795 0.20 1
## delightful 10 0.89 0.787 0.21 1
## enjoyable 13 0.88 0.781 0.22 1
## pretty 25 0.88 0.773 0.23 1
## appealing 1 0.88 0.767 0.23 1
## beautiful 5 0.87 0.761 0.24 1
## nice 22 0.87 0.760 0.24 1
## motivating 21 0.84 0.706 0.29 1
## inviting 18 0.84 0.703 0.30 1
## lovely 20 0.83 0.693 0.31 1
## elegant 11 0.83 0.691 0.31 1
## engaging 12 0.82 0.674 0.33 1
## exciting 14 0.81 0.657 0.34 1
## fascinating 15 0.80 0.647 0.35 1
## tasteful 30 0.80 0.642 0.36 1
## harmonious 16 0.74 0.550 0.45 1
## sophisticated 29 0.73 0.529 0.47 1
## interesting 17 0.73 0.527 0.47 1
## artistic 2 0.69 0.471 0.53 1
## wellDesigned 31 0.69 0.471 0.53 1
## clean 6 0.66 0.432 0.57 1
## creative 9 0.66 0.430 0.57 1
## professional 26 0.60 0.355 0.64 1
## balanced 4 0.59 0.344 0.66 1
## organized 23 0.55 0.304 0.70 1
## colorHarmonious 8 0.48 0.227 0.77 1
## cluttered 7 0.27 0.072 0.93 1
## provoking 27 0.19 0.037 0.96 1
##
## PA1
## SS loadings 18.01
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 434 and the objective function was 6.4
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.97
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.78 0.16 0.63 0.37 1.1
## elegant 11 0.72 0.46 0.72 0.28 1.7
## organized 23 0.72 0.06 0.52 0.48 1.0
## satisfying 28 0.69 0.59 0.82 0.18 2.0
## pleasing 24 0.67 0.60 0.80 0.20 2.0
## professional 26 0.64 0.20 0.45 0.55 1.2
## motivating 21 0.63 0.55 0.71 0.29 2.0
## delightful 10 0.63 0.63 0.79 0.21 2.0
## wellDesigned 31 0.63 0.34 0.51 0.49 1.5
## harmonious 16 0.62 0.43 0.57 0.43 1.8
## nice 22 0.62 0.61 0.76 0.24 2.0
## tasteful 30 0.60 0.53 0.64 0.36 2.0
## lovely 20 0.60 0.58 0.69 0.31 2.0
## inviting 18 0.60 0.59 0.70 0.30 2.0
## balanced 4 0.59 0.23 0.41 0.59 1.3
## sophisticated 29 0.58 0.45 0.54 0.46 1.9
## colorHarmonious 8 0.38 0.30 0.23 0.77 1.9
## cluttered 7 0.34 0.04 0.12 0.88 1.0
## fascinating 15 0.36 0.79 0.76 0.24 1.4
## interesting 17 0.29 0.75 0.64 0.36 1.3
## creative 9 0.20 0.74 0.59 0.41 1.1
## artistic 2 0.25 0.74 0.60 0.40 1.2
## exciting 14 0.47 0.68 0.68 0.32 1.8
## beautiful 5 0.57 0.67 0.77 0.23 1.9
## engaging 12 0.50 0.66 0.69 0.31 1.9
## pretty 25 0.59 0.65 0.77 0.23 2.0
## enjoyable 13 0.60 0.65 0.78 0.22 2.0
## likable 19 0.62 0.65 0.81 0.19 2.0
## attractive 3 0.62 0.64 0.79 0.21 2.0
## appealing 1 0.62 0.62 0.77 0.23 2.0
## provoking 27 -0.11 0.39 0.16 0.84 1.2
##
## PA1 PA2
## SS loadings 9.90 9.50
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.94
## Multiple R square of scores with factors 0.88 0.88
## Minimum correlation of possible factor scores 0.75 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.92 -0.21 0.63 0.37 1.1
## organized 23 0.89 -0.29 0.52 0.48 1.2
## professional 26 0.73 -0.08 0.45 0.55 1.0
## elegant 11 0.69 0.21 0.72 0.28 1.2
## balanced 4 0.65 -0.01 0.41 0.59 1.0
## wellDesigned 31 0.63 0.11 0.51 0.49 1.1
## satisfying 28 0.58 0.40 0.82 0.18 1.8
## harmonious 16 0.58 0.22 0.57 0.43 1.3
## pleasing 24 0.55 0.42 0.80 0.20 1.9
## motivating 21 0.52 0.39 0.71 0.29 1.8
## sophisticated 29 0.51 0.27 0.54 0.46 1.5
## tasteful 30 0.50 0.37 0.64 0.36 1.8
## nice 22 0.47 0.47 0.76 0.24 2.0
## lovely 20 0.46 0.44 0.69 0.31 2.0
## inviting 18 0.46 0.45 0.70 0.30 2.0
## cluttered 7 0.42 -0.13 0.12 0.88 1.2
## colorHarmonious 8 0.33 0.18 0.23 0.77 1.6
## creative 9 -0.14 0.86 0.59 0.41 1.1
## fascinating 15 0.04 0.84 0.76 0.24 1.0
## artistic 2 -0.07 0.83 0.60 0.40 1.0
## interesting 17 -0.02 0.82 0.64 0.36 1.0
## exciting 14 0.25 0.63 0.68 0.32 1.3
## engaging 12 0.29 0.60 0.69 0.31 1.4
## beautiful 5 0.38 0.57 0.77 0.23 1.7
## provoking 27 -0.35 0.56 0.16 0.84 1.7
## pretty 25 0.42 0.54 0.77 0.23 1.9
## enjoyable 13 0.43 0.53 0.78 0.22 1.9
## likable 19 0.46 0.51 0.81 0.19 2.0
## attractive 3 0.46 0.51 0.79 0.21 2.0
## delightful 10 0.48 0.48 0.79 0.21 2.0
## appealing 1 0.47 0.48 0.77 0.23 2.0
##
## PA1 PA2
## SS loadings 9.93 9.48
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.0 0.7
## PA2 0.7 1.0
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.95 0.95
## Minimum correlation of possible factor scores 0.90 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## satisfying 28 0.90 0.813 0.19 1
## likable 19 0.90 0.807 0.19 1
## pleasing 24 0.90 0.803 0.20 1
## attractive 3 0.89 0.795 0.20 1
## delightful 10 0.89 0.787 0.21 1
## enjoyable 13 0.88 0.781 0.22 1
## pretty 25 0.88 0.773 0.23 1
## appealing 1 0.88 0.767 0.23 1
## beautiful 5 0.87 0.761 0.24 1
## nice 22 0.87 0.760 0.24 1
## motivating 21 0.84 0.706 0.29 1
## inviting 18 0.84 0.703 0.30 1
## lovely 20 0.83 0.693 0.31 1
## elegant 11 0.83 0.691 0.31 1
## engaging 12 0.82 0.674 0.33 1
## exciting 14 0.81 0.657 0.34 1
## fascinating 15 0.80 0.647 0.35 1
## tasteful 30 0.80 0.642 0.36 1
## harmonious 16 0.74 0.550 0.45 1
## sophisticated 29 0.73 0.529 0.47 1
## interesting 17 0.73 0.527 0.47 1
## artistic 2 0.69 0.471 0.53 1
## wellDesigned 31 0.69 0.471 0.53 1
## clean 6 0.66 0.432 0.57 1
## creative 9 0.66 0.430 0.57 1
## professional 26 0.60 0.355 0.64 1
## balanced 4 0.59 0.344 0.66 1
## organized 23 0.55 0.304 0.70 1
## colorHarmonious 8 0.48 0.227 0.77 1
## cluttered 7 0.27 0.072 0.93 1
## provoking 27 0.19 0.037 0.96 1
##
## PA1
## SS loadings 18.01
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 434 and the objective function was 6.4
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.97
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.78 0.16 0.63 0.37 1.1
## elegant 11 0.72 0.46 0.72 0.28 1.7
## organized 23 0.72 0.06 0.52 0.48 1.0
## satisfying 28 0.69 0.59 0.82 0.18 2.0
## pleasing 24 0.67 0.60 0.80 0.20 2.0
## professional 26 0.64 0.20 0.45 0.55 1.2
## motivating 21 0.63 0.55 0.71 0.29 2.0
## delightful 10 0.63 0.63 0.79 0.21 2.0
## wellDesigned 31 0.63 0.34 0.51 0.49 1.5
## harmonious 16 0.62 0.43 0.57 0.43 1.8
## nice 22 0.62 0.61 0.76 0.24 2.0
## tasteful 30 0.60 0.53 0.64 0.36 2.0
## lovely 20 0.60 0.58 0.69 0.31 2.0
## inviting 18 0.60 0.59 0.70 0.30 2.0
## balanced 4 0.59 0.23 0.41 0.59 1.3
## sophisticated 29 0.58 0.45 0.54 0.46 1.9
## colorHarmonious 8 0.38 0.30 0.23 0.77 1.9
## cluttered 7 0.34 0.04 0.12 0.88 1.0
## fascinating 15 0.36 0.79 0.76 0.24 1.4
## interesting 17 0.29 0.75 0.64 0.36 1.3
## creative 9 0.20 0.74 0.59 0.41 1.1
## artistic 2 0.25 0.74 0.60 0.40 1.2
## exciting 14 0.47 0.68 0.68 0.32 1.8
## beautiful 5 0.57 0.67 0.77 0.23 1.9
## engaging 12 0.50 0.66 0.69 0.31 1.9
## pretty 25 0.59 0.65 0.77 0.23 2.0
## enjoyable 13 0.60 0.65 0.78 0.22 2.0
## likable 19 0.62 0.65 0.81 0.19 2.0
## attractive 3 0.62 0.64 0.79 0.21 2.0
## appealing 1 0.62 0.62 0.77 0.23 2.0
## provoking 27 -0.11 0.39 0.16 0.84 1.2
##
## PA1 PA2
## SS loadings 9.90 9.50
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.94
## Multiple R square of scores with factors 0.88 0.88
## Minimum correlation of possible factor scores 0.75 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.92 -0.21 0.63 0.37 1.1
## organized 23 0.89 -0.29 0.52 0.48 1.2
## professional 26 0.73 -0.08 0.45 0.55 1.0
## elegant 11 0.69 0.21 0.72 0.28 1.2
## balanced 4 0.65 -0.01 0.41 0.59 1.0
## wellDesigned 31 0.63 0.11 0.51 0.49 1.1
## satisfying 28 0.58 0.40 0.82 0.18 1.8
## harmonious 16 0.58 0.22 0.57 0.43 1.3
## pleasing 24 0.55 0.42 0.80 0.20 1.9
## motivating 21 0.52 0.39 0.71 0.29 1.8
## sophisticated 29 0.51 0.27 0.54 0.46 1.5
## tasteful 30 0.50 0.37 0.64 0.36 1.8
## nice 22 0.47 0.47 0.76 0.24 2.0
## lovely 20 0.46 0.44 0.69 0.31 2.0
## inviting 18 0.46 0.45 0.70 0.30 2.0
## cluttered 7 0.42 -0.13 0.12 0.88 1.2
## colorHarmonious 8 0.33 0.18 0.23 0.77 1.6
## creative 9 -0.14 0.86 0.59 0.41 1.1
## fascinating 15 0.04 0.84 0.76 0.24 1.0
## artistic 2 -0.07 0.83 0.60 0.40 1.0
## interesting 17 -0.02 0.82 0.64 0.36 1.0
## exciting 14 0.25 0.63 0.68 0.32 1.3
## engaging 12 0.29 0.60 0.69 0.31 1.4
## beautiful 5 0.38 0.57 0.77 0.23 1.7
## provoking 27 -0.35 0.56 0.16 0.84 1.7
## pretty 25 0.42 0.54 0.77 0.23 1.9
## enjoyable 13 0.43 0.53 0.78 0.22 1.9
## likable 19 0.46 0.51 0.81 0.19 2.0
## attractive 3 0.46 0.51 0.79 0.21 2.0
## delightful 10 0.48 0.48 0.79 0.21 2.0
## appealing 1 0.47 0.48 0.77 0.23 2.0
##
## PA1 PA2
## SS loadings 9.93 9.48
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.0 0.7
## PA2 0.7 1.0
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.95 0.95
## Minimum correlation of possible factor scores 0.90 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## satisfying 28 0.90 0.813 0.19 1
## likable 19 0.90 0.807 0.19 1
## pleasing 24 0.90 0.803 0.20 1
## attractive 3 0.89 0.795 0.20 1
## delightful 10 0.89 0.787 0.21 1
## enjoyable 13 0.88 0.781 0.22 1
## pretty 25 0.88 0.773 0.23 1
## appealing 1 0.88 0.767 0.23 1
## beautiful 5 0.87 0.761 0.24 1
## nice 22 0.87 0.760 0.24 1
## motivating 21 0.84 0.706 0.29 1
## inviting 18 0.84 0.703 0.30 1
## lovely 20 0.83 0.693 0.31 1
## elegant 11 0.83 0.691 0.31 1
## engaging 12 0.82 0.674 0.33 1
## exciting 14 0.81 0.657 0.34 1
## fascinating 15 0.80 0.647 0.35 1
## tasteful 30 0.80 0.642 0.36 1
## harmonious 16 0.74 0.550 0.45 1
## sophisticated 29 0.73 0.529 0.47 1
## interesting 17 0.73 0.527 0.47 1
## artistic 2 0.69 0.471 0.53 1
## wellDesigned 31 0.69 0.471 0.53 1
## clean 6 0.66 0.432 0.57 1
## creative 9 0.66 0.430 0.57 1
## professional 26 0.60 0.355 0.64 1
## balanced 4 0.59 0.344 0.66 1
## organized 23 0.55 0.304 0.70 1
## colorHarmonious 8 0.48 0.227 0.77 1
## cluttered 7 0.27 0.072 0.93 1
## provoking 27 0.19 0.037 0.96 1
##
## PA1
## SS loadings 18.01
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 434 and the objective function was 6.4
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.97
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.78 0.16 0.63 0.37 1.1
## elegant 11 0.72 0.46 0.72 0.28 1.7
## organized 23 0.72 0.06 0.52 0.48 1.0
## satisfying 28 0.69 0.59 0.82 0.18 2.0
## pleasing 24 0.67 0.60 0.80 0.20 2.0
## professional 26 0.64 0.20 0.45 0.55 1.2
## motivating 21 0.63 0.55 0.71 0.29 2.0
## delightful 10 0.63 0.63 0.79 0.21 2.0
## wellDesigned 31 0.63 0.34 0.51 0.49 1.5
## harmonious 16 0.62 0.43 0.57 0.43 1.8
## nice 22 0.62 0.61 0.76 0.24 2.0
## tasteful 30 0.60 0.53 0.64 0.36 2.0
## lovely 20 0.60 0.58 0.69 0.31 2.0
## inviting 18 0.60 0.59 0.70 0.30 2.0
## balanced 4 0.59 0.23 0.41 0.59 1.3
## sophisticated 29 0.58 0.45 0.54 0.46 1.9
## colorHarmonious 8 0.38 0.30 0.23 0.77 1.9
## cluttered 7 0.34 0.04 0.12 0.88 1.0
## fascinating 15 0.36 0.79 0.76 0.24 1.4
## interesting 17 0.29 0.75 0.64 0.36 1.3
## creative 9 0.20 0.74 0.59 0.41 1.1
## artistic 2 0.25 0.74 0.60 0.40 1.2
## exciting 14 0.47 0.68 0.68 0.32 1.8
## beautiful 5 0.57 0.67 0.77 0.23 1.9
## engaging 12 0.50 0.66 0.69 0.31 1.9
## pretty 25 0.59 0.65 0.77 0.23 2.0
## enjoyable 13 0.60 0.65 0.78 0.22 2.0
## likable 19 0.62 0.65 0.81 0.19 2.0
## attractive 3 0.62 0.64 0.79 0.21 2.0
## appealing 1 0.62 0.62 0.77 0.23 2.0
## provoking 27 -0.11 0.39 0.16 0.84 1.2
##
## PA1 PA2
## SS loadings 9.90 9.50
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.94 0.94
## Multiple R square of scores with factors 0.88 0.88
## Minimum correlation of possible factor scores 0.75 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## clean 6 0.92 -0.21 0.63 0.37 1.1
## organized 23 0.89 -0.29 0.52 0.48 1.2
## professional 26 0.73 -0.08 0.45 0.55 1.0
## elegant 11 0.69 0.21 0.72 0.28 1.2
## balanced 4 0.65 -0.01 0.41 0.59 1.0
## wellDesigned 31 0.63 0.11 0.51 0.49 1.1
## satisfying 28 0.58 0.40 0.82 0.18 1.8
## harmonious 16 0.58 0.22 0.57 0.43 1.3
## pleasing 24 0.55 0.42 0.80 0.20 1.9
## motivating 21 0.52 0.39 0.71 0.29 1.8
## sophisticated 29 0.51 0.27 0.54 0.46 1.5
## tasteful 30 0.50 0.37 0.64 0.36 1.8
## nice 22 0.47 0.47 0.76 0.24 2.0
## lovely 20 0.46 0.44 0.69 0.31 2.0
## inviting 18 0.46 0.45 0.70 0.30 2.0
## cluttered 7 0.42 -0.13 0.12 0.88 1.2
## colorHarmonious 8 0.33 0.18 0.23 0.77 1.6
## creative 9 -0.14 0.86 0.59 0.41 1.1
## fascinating 15 0.04 0.84 0.76 0.24 1.0
## artistic 2 -0.07 0.83 0.60 0.40 1.0
## interesting 17 -0.02 0.82 0.64 0.36 1.0
## exciting 14 0.25 0.63 0.68 0.32 1.3
## engaging 12 0.29 0.60 0.69 0.31 1.4
## beautiful 5 0.38 0.57 0.77 0.23 1.7
## provoking 27 -0.35 0.56 0.16 0.84 1.7
## pretty 25 0.42 0.54 0.77 0.23 1.9
## enjoyable 13 0.43 0.53 0.78 0.22 1.9
## likable 19 0.46 0.51 0.81 0.19 2.0
## attractive 3 0.46 0.51 0.79 0.21 2.0
## delightful 10 0.48 0.48 0.79 0.21 2.0
## appealing 1 0.47 0.48 0.77 0.23 2.0
##
## PA1 PA2
## SS loadings 9.93 9.48
## Proportion Var 0.32 0.31
## Cumulative Var 0.32 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.0 0.7
## PA2 0.7 1.0
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 33.25
## The degrees of freedom for the model are 404 and the objective function was 5.07
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.95 0.95
## Minimum correlation of possible factor scores 0.90 0.91
##
##
## ## Image 8
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.77 0.23 1
## enjoyable 13 0.87 0.76 0.24 1
## nice 22 0.87 0.76 0.24 1
## inviting 18 0.85 0.72 0.28 1
## appealing 1 0.85 0.72 0.28 1
## pleasing 24 0.84 0.71 0.29 1
## attractive 3 0.84 0.70 0.30 1
## engaging 12 0.83 0.69 0.31 1
## delightful 10 0.82 0.67 0.33 1
## lovely 20 0.81 0.66 0.34 1
## beautiful 5 0.81 0.65 0.35 1
## tasteful 30 0.81 0.65 0.35 1
## satisfying 28 0.80 0.65 0.35 1
## pretty 25 0.79 0.63 0.37 1
## exciting 14 0.77 0.59 0.41 1
## motivating 21 0.75 0.56 0.44 1
## interesting 17 0.74 0.55 0.45 1
## harmonious 16 0.74 0.55 0.45 1
## fascinating 15 0.71 0.50 0.50 1
## wellDesigned 31 0.71 0.50 0.50 1
## balanced 4 0.70 0.49 0.51 1
## creative 9 0.70 0.48 0.52 1
## clean 6 0.70 0.48 0.52 1
## elegant 11 0.69 0.47 0.53 1
## sophisticated 29 0.65 0.43 0.57 1
## artistic 2 0.61 0.37 0.63 1
## organized 23 0.60 0.36 0.64 1
## colorHarmonious 8 0.55 0.30 0.70 1
## professional 26 0.46 0.21 0.79 1
## provoking 27 0.37 0.14 0.86 1
## cluttered 7 0.34 0.11 0.89 1
##
## PA1
## SS loadings 16.86
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 434 and the objective function was 6.18
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## enjoyable 13 0.79 0.39 0.78 0.22 1.5
## engaging 12 0.79 0.34 0.73 0.27 1.4
## exciting 14 0.77 0.25 0.66 0.34 1.2
## appealing 1 0.76 0.40 0.74 0.26 1.5
## inviting 18 0.76 0.40 0.74 0.26 1.5
## likable 19 0.76 0.45 0.78 0.22 1.6
## attractive 3 0.74 0.40 0.72 0.28 1.5
## nice 22 0.72 0.48 0.76 0.24 1.7
## lovely 20 0.72 0.39 0.67 0.33 1.6
## pleasing 24 0.71 0.45 0.72 0.28 1.7
## creative 9 0.71 0.22 0.55 0.45 1.2
## interesting 17 0.70 0.30 0.58 0.42 1.4
## delightful 10 0.70 0.43 0.67 0.33 1.7
## pretty 25 0.70 0.39 0.64 0.36 1.6
## satisfying 28 0.67 0.44 0.65 0.35 1.7
## artistic 2 0.65 0.15 0.45 0.55 1.1
## tasteful 30 0.65 0.48 0.65 0.35 1.8
## beautiful 5 0.64 0.49 0.65 0.35 1.9
## fascinating 15 0.64 0.33 0.51 0.49 1.5
## motivating 21 0.62 0.41 0.56 0.44 1.7
## colorHarmonious 8 0.43 0.34 0.30 0.70 1.9
## provoking 27 0.43 0.04 0.19 0.81 1.0
## wellDesigned 31 0.33 0.76 0.68 0.32 1.4
## elegant 11 0.33 0.72 0.63 0.37 1.4
## professional 26 0.05 0.71 0.51 0.49 1.0
## organized 23 0.23 0.71 0.55 0.45 1.2
## balanced 4 0.37 0.69 0.61 0.39 1.5
## clean 6 0.37 0.68 0.60 0.40 1.5
## harmonious 16 0.47 0.61 0.60 0.40 1.9
## sophisticated 29 0.41 0.54 0.47 0.53 1.9
## cluttered 7 0.18 0.32 0.13 0.87 1.6
##
## PA1 PA2
## SS loadings 11.49 6.98
## Proportion Var 0.37 0.23
## Cumulative Var 0.37 0.60
## Proportion Explained 0.62 0.38
## Cumulative Proportion 0.62 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.93
## Multiple R square of scores with factors 0.92 0.86
## Minimum correlation of possible factor scores 0.84 0.72
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.89 -0.11 0.66 0.34 1.0
## engaging 12 0.86 0.00 0.73 0.27 1.0
## enjoyable 13 0.83 0.07 0.78 0.22 1.0
## creative 9 0.82 -0.11 0.55 0.45 1.0
## appealing 1 0.79 0.09 0.74 0.26 1.0
## inviting 18 0.79 0.09 0.74 0.26 1.0
## artistic 2 0.78 -0.17 0.45 0.55 1.1
## interesting 17 0.77 0.00 0.58 0.42 1.0
## attractive 3 0.76 0.11 0.72 0.28 1.0
## likable 19 0.75 0.17 0.78 0.22 1.1
## lovely 20 0.73 0.12 0.67 0.33 1.0
## pretty 25 0.71 0.11 0.64 0.36 1.1
## pleasing 24 0.70 0.19 0.72 0.28 1.2
## delightful 10 0.69 0.17 0.67 0.33 1.1
## nice 22 0.69 0.23 0.76 0.24 1.2
## fascinating 15 0.66 0.08 0.51 0.49 1.0
## satisfying 28 0.64 0.21 0.65 0.35 1.2
## motivating 21 0.59 0.20 0.56 0.44 1.2
## tasteful 30 0.59 0.27 0.65 0.35 1.4
## beautiful 5 0.58 0.29 0.65 0.35 1.5
## provoking 27 0.55 -0.19 0.19 0.81 1.2
## colorHarmonious 8 0.39 0.20 0.30 0.70 1.5
## professional 26 -0.33 0.91 0.51 0.49 1.3
## wellDesigned 31 0.01 0.82 0.68 0.32 1.0
## organized 23 -0.09 0.81 0.55 0.45 1.0
## elegant 11 0.03 0.78 0.63 0.37 1.0
## balanced 4 0.11 0.70 0.61 0.39 1.0
## clean 6 0.10 0.70 0.60 0.40 1.0
## harmonious 16 0.28 0.55 0.60 0.40 1.5
## sophisticated 29 0.24 0.49 0.47 0.53 1.5
## cluttered 7 0.06 0.32 0.13 0.87 1.1
##
## PA1 PA2
## SS loadings 12.54 5.92
## Proportion Var 0.40 0.19
## Cumulative Var 0.40 0.60
## Proportion Explained 0.68 0.32
## Cumulative Proportion 0.68 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.99 0.96
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.95 0.86
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.77 0.23 1
## enjoyable 13 0.87 0.76 0.24 1
## nice 22 0.87 0.76 0.24 1
## inviting 18 0.85 0.72 0.28 1
## appealing 1 0.85 0.72 0.28 1
## pleasing 24 0.84 0.71 0.29 1
## attractive 3 0.84 0.70 0.30 1
## engaging 12 0.83 0.69 0.31 1
## delightful 10 0.82 0.67 0.33 1
## lovely 20 0.81 0.66 0.34 1
## beautiful 5 0.81 0.65 0.35 1
## tasteful 30 0.81 0.65 0.35 1
## satisfying 28 0.80 0.65 0.35 1
## pretty 25 0.79 0.63 0.37 1
## exciting 14 0.77 0.59 0.41 1
## motivating 21 0.75 0.56 0.44 1
## interesting 17 0.74 0.55 0.45 1
## harmonious 16 0.74 0.55 0.45 1
## fascinating 15 0.71 0.50 0.50 1
## wellDesigned 31 0.71 0.50 0.50 1
## balanced 4 0.70 0.49 0.51 1
## creative 9 0.70 0.48 0.52 1
## clean 6 0.70 0.48 0.52 1
## elegant 11 0.69 0.47 0.53 1
## sophisticated 29 0.65 0.43 0.57 1
## artistic 2 0.61 0.37 0.63 1
## organized 23 0.60 0.36 0.64 1
## colorHarmonious 8 0.55 0.30 0.70 1
## professional 26 0.46 0.21 0.79 1
## provoking 27 0.37 0.14 0.86 1
## cluttered 7 0.34 0.11 0.89 1
##
## PA1
## SS loadings 16.86
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 434 and the objective function was 6.18
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## enjoyable 13 0.79 0.39 0.78 0.22 1.5
## engaging 12 0.79 0.34 0.73 0.27 1.4
## exciting 14 0.77 0.25 0.66 0.34 1.2
## appealing 1 0.76 0.40 0.74 0.26 1.5
## inviting 18 0.76 0.40 0.74 0.26 1.5
## likable 19 0.76 0.45 0.78 0.22 1.6
## attractive 3 0.74 0.40 0.72 0.28 1.5
## nice 22 0.72 0.48 0.76 0.24 1.7
## lovely 20 0.72 0.39 0.67 0.33 1.6
## pleasing 24 0.71 0.45 0.72 0.28 1.7
## creative 9 0.71 0.22 0.55 0.45 1.2
## interesting 17 0.70 0.30 0.58 0.42 1.4
## delightful 10 0.70 0.43 0.67 0.33 1.7
## pretty 25 0.70 0.39 0.64 0.36 1.6
## satisfying 28 0.67 0.44 0.65 0.35 1.7
## artistic 2 0.65 0.15 0.45 0.55 1.1
## tasteful 30 0.65 0.48 0.65 0.35 1.8
## beautiful 5 0.64 0.49 0.65 0.35 1.9
## fascinating 15 0.64 0.33 0.51 0.49 1.5
## motivating 21 0.62 0.41 0.56 0.44 1.7
## colorHarmonious 8 0.43 0.34 0.30 0.70 1.9
## provoking 27 0.43 0.04 0.19 0.81 1.0
## wellDesigned 31 0.33 0.76 0.68 0.32 1.4
## elegant 11 0.33 0.72 0.63 0.37 1.4
## professional 26 0.05 0.71 0.51 0.49 1.0
## organized 23 0.23 0.71 0.55 0.45 1.2
## balanced 4 0.37 0.69 0.61 0.39 1.5
## clean 6 0.37 0.68 0.60 0.40 1.5
## harmonious 16 0.47 0.61 0.60 0.40 1.9
## sophisticated 29 0.41 0.54 0.47 0.53 1.9
## cluttered 7 0.18 0.32 0.13 0.87 1.6
##
## PA1 PA2
## SS loadings 11.49 6.98
## Proportion Var 0.37 0.23
## Cumulative Var 0.37 0.60
## Proportion Explained 0.62 0.38
## Cumulative Proportion 0.62 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.93
## Multiple R square of scores with factors 0.92 0.86
## Minimum correlation of possible factor scores 0.84 0.72
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.89 -0.11 0.66 0.34 1.0
## engaging 12 0.86 0.00 0.73 0.27 1.0
## enjoyable 13 0.83 0.07 0.78 0.22 1.0
## creative 9 0.82 -0.11 0.55 0.45 1.0
## appealing 1 0.79 0.09 0.74 0.26 1.0
## inviting 18 0.79 0.09 0.74 0.26 1.0
## artistic 2 0.78 -0.17 0.45 0.55 1.1
## interesting 17 0.77 0.00 0.58 0.42 1.0
## attractive 3 0.76 0.11 0.72 0.28 1.0
## likable 19 0.75 0.17 0.78 0.22 1.1
## lovely 20 0.73 0.12 0.67 0.33 1.0
## pretty 25 0.71 0.11 0.64 0.36 1.1
## pleasing 24 0.70 0.19 0.72 0.28 1.2
## delightful 10 0.69 0.17 0.67 0.33 1.1
## nice 22 0.69 0.23 0.76 0.24 1.2
## fascinating 15 0.66 0.08 0.51 0.49 1.0
## satisfying 28 0.64 0.21 0.65 0.35 1.2
## motivating 21 0.59 0.20 0.56 0.44 1.2
## tasteful 30 0.59 0.27 0.65 0.35 1.4
## beautiful 5 0.58 0.29 0.65 0.35 1.5
## provoking 27 0.55 -0.19 0.19 0.81 1.2
## colorHarmonious 8 0.39 0.20 0.30 0.70 1.5
## professional 26 -0.33 0.91 0.51 0.49 1.3
## wellDesigned 31 0.01 0.82 0.68 0.32 1.0
## organized 23 -0.09 0.81 0.55 0.45 1.0
## elegant 11 0.03 0.78 0.63 0.37 1.0
## balanced 4 0.11 0.70 0.61 0.39 1.0
## clean 6 0.10 0.70 0.60 0.40 1.0
## harmonious 16 0.28 0.55 0.60 0.40 1.5
## sophisticated 29 0.24 0.49 0.47 0.53 1.5
## cluttered 7 0.06 0.32 0.13 0.87 1.1
##
## PA1 PA2
## SS loadings 12.54 5.92
## Proportion Var 0.40 0.19
## Cumulative Var 0.40 0.60
## Proportion Explained 0.68 0.32
## Cumulative Proportion 0.68 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.99 0.96
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.95 0.86
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.77 0.23 1
## enjoyable 13 0.87 0.76 0.24 1
## nice 22 0.87 0.76 0.24 1
## inviting 18 0.85 0.72 0.28 1
## appealing 1 0.85 0.72 0.28 1
## pleasing 24 0.84 0.71 0.29 1
## attractive 3 0.84 0.70 0.30 1
## engaging 12 0.83 0.69 0.31 1
## delightful 10 0.82 0.67 0.33 1
## lovely 20 0.81 0.66 0.34 1
## beautiful 5 0.81 0.65 0.35 1
## tasteful 30 0.81 0.65 0.35 1
## satisfying 28 0.80 0.65 0.35 1
## pretty 25 0.79 0.63 0.37 1
## exciting 14 0.77 0.59 0.41 1
## motivating 21 0.75 0.56 0.44 1
## interesting 17 0.74 0.55 0.45 1
## harmonious 16 0.74 0.55 0.45 1
## fascinating 15 0.71 0.50 0.50 1
## wellDesigned 31 0.71 0.50 0.50 1
## balanced 4 0.70 0.49 0.51 1
## creative 9 0.70 0.48 0.52 1
## clean 6 0.70 0.48 0.52 1
## elegant 11 0.69 0.47 0.53 1
## sophisticated 29 0.65 0.43 0.57 1
## artistic 2 0.61 0.37 0.63 1
## organized 23 0.60 0.36 0.64 1
## colorHarmonious 8 0.55 0.30 0.70 1
## professional 26 0.46 0.21 0.79 1
## provoking 27 0.37 0.14 0.86 1
## cluttered 7 0.34 0.11 0.89 1
##
## PA1
## SS loadings 16.86
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 434 and the objective function was 6.18
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## enjoyable 13 0.79 0.39 0.78 0.22 1.5
## engaging 12 0.79 0.34 0.73 0.27 1.4
## exciting 14 0.77 0.25 0.66 0.34 1.2
## appealing 1 0.76 0.40 0.74 0.26 1.5
## inviting 18 0.76 0.40 0.74 0.26 1.5
## likable 19 0.76 0.45 0.78 0.22 1.6
## attractive 3 0.74 0.40 0.72 0.28 1.5
## nice 22 0.72 0.48 0.76 0.24 1.7
## lovely 20 0.72 0.39 0.67 0.33 1.6
## pleasing 24 0.71 0.45 0.72 0.28 1.7
## creative 9 0.71 0.22 0.55 0.45 1.2
## interesting 17 0.70 0.30 0.58 0.42 1.4
## delightful 10 0.70 0.43 0.67 0.33 1.7
## pretty 25 0.70 0.39 0.64 0.36 1.6
## satisfying 28 0.67 0.44 0.65 0.35 1.7
## artistic 2 0.65 0.15 0.45 0.55 1.1
## tasteful 30 0.65 0.48 0.65 0.35 1.8
## beautiful 5 0.64 0.49 0.65 0.35 1.9
## fascinating 15 0.64 0.33 0.51 0.49 1.5
## motivating 21 0.62 0.41 0.56 0.44 1.7
## colorHarmonious 8 0.43 0.34 0.30 0.70 1.9
## provoking 27 0.43 0.04 0.19 0.81 1.0
## wellDesigned 31 0.33 0.76 0.68 0.32 1.4
## elegant 11 0.33 0.72 0.63 0.37 1.4
## professional 26 0.05 0.71 0.51 0.49 1.0
## organized 23 0.23 0.71 0.55 0.45 1.2
## balanced 4 0.37 0.69 0.61 0.39 1.5
## clean 6 0.37 0.68 0.60 0.40 1.5
## harmonious 16 0.47 0.61 0.60 0.40 1.9
## sophisticated 29 0.41 0.54 0.47 0.53 1.9
## cluttered 7 0.18 0.32 0.13 0.87 1.6
##
## PA1 PA2
## SS loadings 11.49 6.98
## Proportion Var 0.37 0.23
## Cumulative Var 0.37 0.60
## Proportion Explained 0.62 0.38
## Cumulative Proportion 0.62 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.93
## Multiple R square of scores with factors 0.92 0.86
## Minimum correlation of possible factor scores 0.84 0.72
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.89 -0.11 0.66 0.34 1.0
## engaging 12 0.86 0.00 0.73 0.27 1.0
## enjoyable 13 0.83 0.07 0.78 0.22 1.0
## creative 9 0.82 -0.11 0.55 0.45 1.0
## appealing 1 0.79 0.09 0.74 0.26 1.0
## inviting 18 0.79 0.09 0.74 0.26 1.0
## artistic 2 0.78 -0.17 0.45 0.55 1.1
## interesting 17 0.77 0.00 0.58 0.42 1.0
## attractive 3 0.76 0.11 0.72 0.28 1.0
## likable 19 0.75 0.17 0.78 0.22 1.1
## lovely 20 0.73 0.12 0.67 0.33 1.0
## pretty 25 0.71 0.11 0.64 0.36 1.1
## pleasing 24 0.70 0.19 0.72 0.28 1.2
## delightful 10 0.69 0.17 0.67 0.33 1.1
## nice 22 0.69 0.23 0.76 0.24 1.2
## fascinating 15 0.66 0.08 0.51 0.49 1.0
## satisfying 28 0.64 0.21 0.65 0.35 1.2
## motivating 21 0.59 0.20 0.56 0.44 1.2
## tasteful 30 0.59 0.27 0.65 0.35 1.4
## beautiful 5 0.58 0.29 0.65 0.35 1.5
## provoking 27 0.55 -0.19 0.19 0.81 1.2
## colorHarmonious 8 0.39 0.20 0.30 0.70 1.5
## professional 26 -0.33 0.91 0.51 0.49 1.3
## wellDesigned 31 0.01 0.82 0.68 0.32 1.0
## organized 23 -0.09 0.81 0.55 0.45 1.0
## elegant 11 0.03 0.78 0.63 0.37 1.0
## balanced 4 0.11 0.70 0.61 0.39 1.0
## clean 6 0.10 0.70 0.60 0.40 1.0
## harmonious 16 0.28 0.55 0.60 0.40 1.5
## sophisticated 29 0.24 0.49 0.47 0.53 1.5
## cluttered 7 0.06 0.32 0.13 0.87 1.1
##
## PA1 PA2
## SS loadings 12.54 5.92
## Proportion Var 0.40 0.19
## Cumulative Var 0.40 0.60
## Proportion Explained 0.68 0.32
## Cumulative Proportion 0.68 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.99 0.96
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.95 0.86
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.77 0.23 1
## enjoyable 13 0.87 0.76 0.24 1
## nice 22 0.87 0.76 0.24 1
## inviting 18 0.85 0.72 0.28 1
## appealing 1 0.85 0.72 0.28 1
## pleasing 24 0.84 0.71 0.29 1
## attractive 3 0.84 0.70 0.30 1
## engaging 12 0.83 0.69 0.31 1
## delightful 10 0.82 0.67 0.33 1
## lovely 20 0.81 0.66 0.34 1
## beautiful 5 0.81 0.65 0.35 1
## tasteful 30 0.81 0.65 0.35 1
## satisfying 28 0.80 0.65 0.35 1
## pretty 25 0.79 0.63 0.37 1
## exciting 14 0.77 0.59 0.41 1
## motivating 21 0.75 0.56 0.44 1
## interesting 17 0.74 0.55 0.45 1
## harmonious 16 0.74 0.55 0.45 1
## fascinating 15 0.71 0.50 0.50 1
## wellDesigned 31 0.71 0.50 0.50 1
## balanced 4 0.70 0.49 0.51 1
## creative 9 0.70 0.48 0.52 1
## clean 6 0.70 0.48 0.52 1
## elegant 11 0.69 0.47 0.53 1
## sophisticated 29 0.65 0.43 0.57 1
## artistic 2 0.61 0.37 0.63 1
## organized 23 0.60 0.36 0.64 1
## colorHarmonious 8 0.55 0.30 0.70 1
## professional 26 0.46 0.21 0.79 1
## provoking 27 0.37 0.14 0.86 1
## cluttered 7 0.34 0.11 0.89 1
##
## PA1
## SS loadings 16.86
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 434 and the objective function was 6.18
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## enjoyable 13 0.79 0.39 0.78 0.22 1.5
## engaging 12 0.79 0.34 0.73 0.27 1.4
## exciting 14 0.77 0.25 0.66 0.34 1.2
## appealing 1 0.76 0.40 0.74 0.26 1.5
## inviting 18 0.76 0.40 0.74 0.26 1.5
## likable 19 0.76 0.45 0.78 0.22 1.6
## attractive 3 0.74 0.40 0.72 0.28 1.5
## nice 22 0.72 0.48 0.76 0.24 1.7
## lovely 20 0.72 0.39 0.67 0.33 1.6
## pleasing 24 0.71 0.45 0.72 0.28 1.7
## creative 9 0.71 0.22 0.55 0.45 1.2
## interesting 17 0.70 0.30 0.58 0.42 1.4
## delightful 10 0.70 0.43 0.67 0.33 1.7
## pretty 25 0.70 0.39 0.64 0.36 1.6
## satisfying 28 0.67 0.44 0.65 0.35 1.7
## artistic 2 0.65 0.15 0.45 0.55 1.1
## tasteful 30 0.65 0.48 0.65 0.35 1.8
## beautiful 5 0.64 0.49 0.65 0.35 1.9
## fascinating 15 0.64 0.33 0.51 0.49 1.5
## motivating 21 0.62 0.41 0.56 0.44 1.7
## colorHarmonious 8 0.43 0.34 0.30 0.70 1.9
## provoking 27 0.43 0.04 0.19 0.81 1.0
## wellDesigned 31 0.33 0.76 0.68 0.32 1.4
## elegant 11 0.33 0.72 0.63 0.37 1.4
## professional 26 0.05 0.71 0.51 0.49 1.0
## organized 23 0.23 0.71 0.55 0.45 1.2
## balanced 4 0.37 0.69 0.61 0.39 1.5
## clean 6 0.37 0.68 0.60 0.40 1.5
## harmonious 16 0.47 0.61 0.60 0.40 1.9
## sophisticated 29 0.41 0.54 0.47 0.53 1.9
## cluttered 7 0.18 0.32 0.13 0.87 1.6
##
## PA1 PA2
## SS loadings 11.49 6.98
## Proportion Var 0.37 0.23
## Cumulative Var 0.37 0.60
## Proportion Explained 0.62 0.38
## Cumulative Proportion 0.62 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.93
## Multiple R square of scores with factors 0.92 0.86
## Minimum correlation of possible factor scores 0.84 0.72
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.89 -0.11 0.66 0.34 1.0
## engaging 12 0.86 0.00 0.73 0.27 1.0
## enjoyable 13 0.83 0.07 0.78 0.22 1.0
## creative 9 0.82 -0.11 0.55 0.45 1.0
## appealing 1 0.79 0.09 0.74 0.26 1.0
## inviting 18 0.79 0.09 0.74 0.26 1.0
## artistic 2 0.78 -0.17 0.45 0.55 1.1
## interesting 17 0.77 0.00 0.58 0.42 1.0
## attractive 3 0.76 0.11 0.72 0.28 1.0
## likable 19 0.75 0.17 0.78 0.22 1.1
## lovely 20 0.73 0.12 0.67 0.33 1.0
## pretty 25 0.71 0.11 0.64 0.36 1.1
## pleasing 24 0.70 0.19 0.72 0.28 1.2
## delightful 10 0.69 0.17 0.67 0.33 1.1
## nice 22 0.69 0.23 0.76 0.24 1.2
## fascinating 15 0.66 0.08 0.51 0.49 1.0
## satisfying 28 0.64 0.21 0.65 0.35 1.2
## motivating 21 0.59 0.20 0.56 0.44 1.2
## tasteful 30 0.59 0.27 0.65 0.35 1.4
## beautiful 5 0.58 0.29 0.65 0.35 1.5
## provoking 27 0.55 -0.19 0.19 0.81 1.2
## colorHarmonious 8 0.39 0.20 0.30 0.70 1.5
## professional 26 -0.33 0.91 0.51 0.49 1.3
## wellDesigned 31 0.01 0.82 0.68 0.32 1.0
## organized 23 -0.09 0.81 0.55 0.45 1.0
## elegant 11 0.03 0.78 0.63 0.37 1.0
## balanced 4 0.11 0.70 0.61 0.39 1.0
## clean 6 0.10 0.70 0.60 0.40 1.0
## harmonious 16 0.28 0.55 0.60 0.40 1.5
## sophisticated 29 0.24 0.49 0.47 0.53 1.5
## cluttered 7 0.06 0.32 0.13 0.87 1.1
##
## PA1 PA2
## SS loadings 12.54 5.92
## Proportion Var 0.40 0.19
## Cumulative Var 0.40 0.60
## Proportion Explained 0.68 0.32
## Cumulative Proportion 0.68 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.99 0.96
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.95 0.86
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.88 0.77 0.23 1
## enjoyable 13 0.87 0.76 0.24 1
## nice 22 0.87 0.76 0.24 1
## inviting 18 0.85 0.72 0.28 1
## appealing 1 0.85 0.72 0.28 1
## pleasing 24 0.84 0.71 0.29 1
## attractive 3 0.84 0.70 0.30 1
## engaging 12 0.83 0.69 0.31 1
## delightful 10 0.82 0.67 0.33 1
## lovely 20 0.81 0.66 0.34 1
## beautiful 5 0.81 0.65 0.35 1
## tasteful 30 0.81 0.65 0.35 1
## satisfying 28 0.80 0.65 0.35 1
## pretty 25 0.79 0.63 0.37 1
## exciting 14 0.77 0.59 0.41 1
## motivating 21 0.75 0.56 0.44 1
## interesting 17 0.74 0.55 0.45 1
## harmonious 16 0.74 0.55 0.45 1
## fascinating 15 0.71 0.50 0.50 1
## wellDesigned 31 0.71 0.50 0.50 1
## balanced 4 0.70 0.49 0.51 1
## creative 9 0.70 0.48 0.52 1
## clean 6 0.70 0.48 0.52 1
## elegant 11 0.69 0.47 0.53 1
## sophisticated 29 0.65 0.43 0.57 1
## artistic 2 0.61 0.37 0.63 1
## organized 23 0.60 0.36 0.64 1
## colorHarmonious 8 0.55 0.30 0.70 1
## professional 26 0.46 0.21 0.79 1
## provoking 27 0.37 0.14 0.86 1
## cluttered 7 0.34 0.11 0.89 1
##
## PA1
## SS loadings 16.86
## Proportion Var 0.54
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 434 and the objective function was 6.18
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## enjoyable 13 0.79 0.39 0.78 0.22 1.5
## engaging 12 0.79 0.34 0.73 0.27 1.4
## exciting 14 0.77 0.25 0.66 0.34 1.2
## appealing 1 0.76 0.40 0.74 0.26 1.5
## inviting 18 0.76 0.40 0.74 0.26 1.5
## likable 19 0.76 0.45 0.78 0.22 1.6
## attractive 3 0.74 0.40 0.72 0.28 1.5
## nice 22 0.72 0.48 0.76 0.24 1.7
## lovely 20 0.72 0.39 0.67 0.33 1.6
## pleasing 24 0.71 0.45 0.72 0.28 1.7
## creative 9 0.71 0.22 0.55 0.45 1.2
## interesting 17 0.70 0.30 0.58 0.42 1.4
## delightful 10 0.70 0.43 0.67 0.33 1.7
## pretty 25 0.70 0.39 0.64 0.36 1.6
## satisfying 28 0.67 0.44 0.65 0.35 1.7
## artistic 2 0.65 0.15 0.45 0.55 1.1
## tasteful 30 0.65 0.48 0.65 0.35 1.8
## beautiful 5 0.64 0.49 0.65 0.35 1.9
## fascinating 15 0.64 0.33 0.51 0.49 1.5
## motivating 21 0.62 0.41 0.56 0.44 1.7
## colorHarmonious 8 0.43 0.34 0.30 0.70 1.9
## provoking 27 0.43 0.04 0.19 0.81 1.0
## wellDesigned 31 0.33 0.76 0.68 0.32 1.4
## elegant 11 0.33 0.72 0.63 0.37 1.4
## professional 26 0.05 0.71 0.51 0.49 1.0
## organized 23 0.23 0.71 0.55 0.45 1.2
## balanced 4 0.37 0.69 0.61 0.39 1.5
## clean 6 0.37 0.68 0.60 0.40 1.5
## harmonious 16 0.47 0.61 0.60 0.40 1.9
## sophisticated 29 0.41 0.54 0.47 0.53 1.9
## cluttered 7 0.18 0.32 0.13 0.87 1.6
##
## PA1 PA2
## SS loadings 11.49 6.98
## Proportion Var 0.37 0.23
## Cumulative Var 0.37 0.60
## Proportion Explained 0.62 0.38
## Cumulative Proportion 0.62 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.93
## Multiple R square of scores with factors 0.92 0.86
## Minimum correlation of possible factor scores 0.84 0.72
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.89 -0.11 0.66 0.34 1.0
## engaging 12 0.86 0.00 0.73 0.27 1.0
## enjoyable 13 0.83 0.07 0.78 0.22 1.0
## creative 9 0.82 -0.11 0.55 0.45 1.0
## appealing 1 0.79 0.09 0.74 0.26 1.0
## inviting 18 0.79 0.09 0.74 0.26 1.0
## artistic 2 0.78 -0.17 0.45 0.55 1.1
## interesting 17 0.77 0.00 0.58 0.42 1.0
## attractive 3 0.76 0.11 0.72 0.28 1.0
## likable 19 0.75 0.17 0.78 0.22 1.1
## lovely 20 0.73 0.12 0.67 0.33 1.0
## pretty 25 0.71 0.11 0.64 0.36 1.1
## pleasing 24 0.70 0.19 0.72 0.28 1.2
## delightful 10 0.69 0.17 0.67 0.33 1.1
## nice 22 0.69 0.23 0.76 0.24 1.2
## fascinating 15 0.66 0.08 0.51 0.49 1.0
## satisfying 28 0.64 0.21 0.65 0.35 1.2
## motivating 21 0.59 0.20 0.56 0.44 1.2
## tasteful 30 0.59 0.27 0.65 0.35 1.4
## beautiful 5 0.58 0.29 0.65 0.35 1.5
## provoking 27 0.55 -0.19 0.19 0.81 1.2
## colorHarmonious 8 0.39 0.20 0.30 0.70 1.5
## professional 26 -0.33 0.91 0.51 0.49 1.3
## wellDesigned 31 0.01 0.82 0.68 0.32 1.0
## organized 23 -0.09 0.81 0.55 0.45 1.0
## elegant 11 0.03 0.78 0.63 0.37 1.0
## balanced 4 0.11 0.70 0.61 0.39 1.0
## clean 6 0.10 0.70 0.60 0.40 1.0
## harmonious 16 0.28 0.55 0.60 0.40 1.5
## sophisticated 29 0.24 0.49 0.47 0.53 1.5
## cluttered 7 0.06 0.32 0.13 0.87 1.1
##
## PA1 PA2
## SS loadings 12.54 5.92
## Proportion Var 0.40 0.19
## Cumulative Var 0.40 0.60
## Proportion Explained 0.68 0.32
## Cumulative Proportion 0.68 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 28.96
## The degrees of freedom for the model are 404 and the objective function was 4.46
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.99 0.96
## Multiple R square of scores with factors 0.97 0.93
## Minimum correlation of possible factor scores 0.95 0.86
##
##
## ## Image 9
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.85 0.72 0.28 1
## attractive 3 0.84 0.71 0.29 1
## enjoyable 13 0.84 0.71 0.29 1
## likable 19 0.84 0.71 0.29 1
## satisfying 28 0.82 0.68 0.32 1
## nice 22 0.81 0.66 0.34 1
## tasteful 30 0.81 0.65 0.35 1
## pleasing 24 0.80 0.65 0.35 1
## delightful 10 0.79 0.62 0.38 1
## inviting 18 0.78 0.61 0.39 1
## pretty 25 0.76 0.58 0.42 1
## beautiful 5 0.76 0.57 0.43 1
## motivating 21 0.75 0.56 0.44 1
## lovely 20 0.74 0.54 0.46 1
## engaging 12 0.74 0.54 0.46 1
## wellDesigned 31 0.73 0.53 0.47 1
## fascinating 15 0.72 0.51 0.49 1
## elegant 11 0.71 0.50 0.50 1
## exciting 14 0.70 0.49 0.51 1
## harmonious 16 0.69 0.48 0.52 1
## sophisticated 29 0.66 0.43 0.57 1
## balanced 4 0.65 0.42 0.58 1
## creative 9 0.62 0.39 0.61 1
## interesting 17 0.61 0.37 0.63 1
## clean 6 0.60 0.36 0.64 1
## organized 23 0.59 0.35 0.65 1
## artistic 2 0.56 0.32 0.68 1
## professional 26 0.50 0.25 0.75 1
## colorHarmonious 8 0.43 0.19 0.81 1
## cluttered 7 0.41 0.17 0.83 1
## provoking 27 0.32 0.10 0.90 1
##
## PA1
## SS loadings 15.38
## Proportion Var 0.50
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 434 and the objective function was 6.37
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## attractive 3 0.75 0.42 0.74 0.26 1.6
## pretty 25 0.75 0.30 0.65 0.35 1.3
## artistic 2 0.74 0.01 0.54 0.46 1.0
## creative 9 0.70 0.14 0.51 0.49 1.1
## beautiful 5 0.69 0.36 0.60 0.40 1.5
## fascinating 15 0.69 0.30 0.56 0.44 1.4
## enjoyable 13 0.68 0.50 0.71 0.29 1.8
## exciting 14 0.68 0.28 0.54 0.46 1.3
## appealing 1 0.67 0.52 0.72 0.28 1.9
## delightful 10 0.67 0.43 0.63 0.37 1.7
## likable 19 0.67 0.51 0.71 0.29 1.9
## lovely 20 0.65 0.38 0.56 0.44 1.6
## inviting 18 0.64 0.45 0.62 0.38 1.8
## nice 22 0.64 0.50 0.66 0.34 1.9
## engaging 12 0.63 0.40 0.55 0.45 1.7
## motivating 21 0.62 0.43 0.57 0.43 1.8
## pleasing 24 0.58 0.55 0.65 0.35 2.0
## interesting 17 0.57 0.26 0.40 0.60 1.4
## provoking 27 0.35 0.08 0.13 0.87 1.1
## clean 6 0.14 0.78 0.63 0.37 1.1
## professional 26 0.05 0.73 0.54 0.46 1.0
## organized 23 0.18 0.71 0.53 0.47 1.1
## wellDesigned 31 0.38 0.68 0.61 0.39 1.6
## balanced 4 0.29 0.67 0.53 0.47 1.4
## harmonious 16 0.37 0.64 0.55 0.45 1.6
## satisfying 28 0.56 0.61 0.69 0.31 2.0
## tasteful 30 0.54 0.61 0.66 0.34 2.0
## elegant 11 0.44 0.58 0.53 0.47 1.9
## sophisticated 29 0.40 0.55 0.46 0.54 1.8
## cluttered 7 0.22 0.37 0.18 0.82 1.6
## colorHarmonious 8 0.30 0.32 0.19 0.81 2.0
##
## PA1 PA2
## SS loadings 9.70 7.45
## Proportion Var 0.31 0.24
## Cumulative Var 0.31 0.55
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.81 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.97 -0.40 0.54 0.46 1.3
## creative 9 0.85 -0.20 0.51 0.49 1.1
## pretty 25 0.82 -0.03 0.65 0.35 1.0
## attractive 3 0.76 0.13 0.74 0.26 1.1
## exciting 14 0.75 -0.02 0.54 0.46 1.0
## fascinating 15 0.74 0.01 0.56 0.44 1.0
## beautiful 5 0.71 0.09 0.60 0.40 1.0
## delightful 10 0.64 0.20 0.63 0.37 1.2
## lovely 20 0.64 0.14 0.56 0.44 1.1
## enjoyable 13 0.62 0.28 0.71 0.29 1.4
## interesting 17 0.61 0.03 0.40 0.60 1.0
## engaging 12 0.61 0.18 0.55 0.45 1.2
## inviting 18 0.60 0.23 0.62 0.38 1.3
## likable 19 0.60 0.30 0.71 0.29 1.5
## appealing 1 0.59 0.31 0.72 0.28 1.5
## motivating 21 0.58 0.22 0.57 0.43 1.3
## nice 22 0.57 0.30 0.66 0.34 1.5
## pleasing 24 0.47 0.40 0.65 0.35 2.0
## provoking 27 0.42 -0.10 0.13 0.87 1.1
## clean 6 -0.25 0.95 0.63 0.37 1.1
## professional 26 -0.34 0.94 0.54 0.46 1.3
## organized 23 -0.15 0.83 0.53 0.47 1.1
## balanced 4 0.01 0.72 0.53 0.47 1.0
## wellDesigned 31 0.12 0.69 0.61 0.39 1.1
## harmonious 16 0.13 0.64 0.55 0.45 1.1
## elegant 11 0.26 0.52 0.53 0.47 1.5
## sophisticated 29 0.22 0.50 0.46 0.54 1.4
## tasteful 30 0.38 0.50 0.66 0.34 1.9
## satisfying 28 0.40 0.49 0.69 0.31 1.9
## cluttered 7 0.09 0.36 0.18 0.82 1.1
## colorHarmonious 8 0.21 0.26 0.19 0.81 1.9
##
## PA1 PA2
## SS loadings 10.21 6.94
## Proportion Var 0.33 0.22
## Cumulative Var 0.33 0.55
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.85 0.72 0.28 1
## attractive 3 0.84 0.71 0.29 1
## enjoyable 13 0.84 0.71 0.29 1
## likable 19 0.84 0.71 0.29 1
## satisfying 28 0.82 0.68 0.32 1
## nice 22 0.81 0.66 0.34 1
## tasteful 30 0.81 0.65 0.35 1
## pleasing 24 0.80 0.65 0.35 1
## delightful 10 0.79 0.62 0.38 1
## inviting 18 0.78 0.61 0.39 1
## pretty 25 0.76 0.58 0.42 1
## beautiful 5 0.76 0.57 0.43 1
## motivating 21 0.75 0.56 0.44 1
## lovely 20 0.74 0.54 0.46 1
## engaging 12 0.74 0.54 0.46 1
## wellDesigned 31 0.73 0.53 0.47 1
## fascinating 15 0.72 0.51 0.49 1
## elegant 11 0.71 0.50 0.50 1
## exciting 14 0.70 0.49 0.51 1
## harmonious 16 0.69 0.48 0.52 1
## sophisticated 29 0.66 0.43 0.57 1
## balanced 4 0.65 0.42 0.58 1
## creative 9 0.62 0.39 0.61 1
## interesting 17 0.61 0.37 0.63 1
## clean 6 0.60 0.36 0.64 1
## organized 23 0.59 0.35 0.65 1
## artistic 2 0.56 0.32 0.68 1
## professional 26 0.50 0.25 0.75 1
## colorHarmonious 8 0.43 0.19 0.81 1
## cluttered 7 0.41 0.17 0.83 1
## provoking 27 0.32 0.10 0.90 1
##
## PA1
## SS loadings 15.38
## Proportion Var 0.50
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 434 and the objective function was 6.37
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## attractive 3 0.75 0.42 0.74 0.26 1.6
## pretty 25 0.75 0.30 0.65 0.35 1.3
## artistic 2 0.74 0.01 0.54 0.46 1.0
## creative 9 0.70 0.14 0.51 0.49 1.1
## beautiful 5 0.69 0.36 0.60 0.40 1.5
## fascinating 15 0.69 0.30 0.56 0.44 1.4
## enjoyable 13 0.68 0.50 0.71 0.29 1.8
## exciting 14 0.68 0.28 0.54 0.46 1.3
## appealing 1 0.67 0.52 0.72 0.28 1.9
## delightful 10 0.67 0.43 0.63 0.37 1.7
## likable 19 0.67 0.51 0.71 0.29 1.9
## lovely 20 0.65 0.38 0.56 0.44 1.6
## inviting 18 0.64 0.45 0.62 0.38 1.8
## nice 22 0.64 0.50 0.66 0.34 1.9
## engaging 12 0.63 0.40 0.55 0.45 1.7
## motivating 21 0.62 0.43 0.57 0.43 1.8
## pleasing 24 0.58 0.55 0.65 0.35 2.0
## interesting 17 0.57 0.26 0.40 0.60 1.4
## provoking 27 0.35 0.08 0.13 0.87 1.1
## clean 6 0.14 0.78 0.63 0.37 1.1
## professional 26 0.05 0.73 0.54 0.46 1.0
## organized 23 0.18 0.71 0.53 0.47 1.1
## wellDesigned 31 0.38 0.68 0.61 0.39 1.6
## balanced 4 0.29 0.67 0.53 0.47 1.4
## harmonious 16 0.37 0.64 0.55 0.45 1.6
## satisfying 28 0.56 0.61 0.69 0.31 2.0
## tasteful 30 0.54 0.61 0.66 0.34 2.0
## elegant 11 0.44 0.58 0.53 0.47 1.9
## sophisticated 29 0.40 0.55 0.46 0.54 1.8
## cluttered 7 0.22 0.37 0.18 0.82 1.6
## colorHarmonious 8 0.30 0.32 0.19 0.81 2.0
##
## PA1 PA2
## SS loadings 9.70 7.45
## Proportion Var 0.31 0.24
## Cumulative Var 0.31 0.55
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.81 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.97 -0.40 0.54 0.46 1.3
## creative 9 0.85 -0.20 0.51 0.49 1.1
## pretty 25 0.82 -0.03 0.65 0.35 1.0
## attractive 3 0.76 0.13 0.74 0.26 1.1
## exciting 14 0.75 -0.02 0.54 0.46 1.0
## fascinating 15 0.74 0.01 0.56 0.44 1.0
## beautiful 5 0.71 0.09 0.60 0.40 1.0
## delightful 10 0.64 0.20 0.63 0.37 1.2
## lovely 20 0.64 0.14 0.56 0.44 1.1
## enjoyable 13 0.62 0.28 0.71 0.29 1.4
## interesting 17 0.61 0.03 0.40 0.60 1.0
## engaging 12 0.61 0.18 0.55 0.45 1.2
## inviting 18 0.60 0.23 0.62 0.38 1.3
## likable 19 0.60 0.30 0.71 0.29 1.5
## appealing 1 0.59 0.31 0.72 0.28 1.5
## motivating 21 0.58 0.22 0.57 0.43 1.3
## nice 22 0.57 0.30 0.66 0.34 1.5
## pleasing 24 0.47 0.40 0.65 0.35 2.0
## provoking 27 0.42 -0.10 0.13 0.87 1.1
## clean 6 -0.25 0.95 0.63 0.37 1.1
## professional 26 -0.34 0.94 0.54 0.46 1.3
## organized 23 -0.15 0.83 0.53 0.47 1.1
## balanced 4 0.01 0.72 0.53 0.47 1.0
## wellDesigned 31 0.12 0.69 0.61 0.39 1.1
## harmonious 16 0.13 0.64 0.55 0.45 1.1
## elegant 11 0.26 0.52 0.53 0.47 1.5
## sophisticated 29 0.22 0.50 0.46 0.54 1.4
## tasteful 30 0.38 0.50 0.66 0.34 1.9
## satisfying 28 0.40 0.49 0.69 0.31 1.9
## cluttered 7 0.09 0.36 0.18 0.82 1.1
## colorHarmonious 8 0.21 0.26 0.19 0.81 1.9
##
## PA1 PA2
## SS loadings 10.21 6.94
## Proportion Var 0.33 0.22
## Cumulative Var 0.33 0.55
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.85 0.72 0.28 1
## attractive 3 0.84 0.71 0.29 1
## enjoyable 13 0.84 0.71 0.29 1
## likable 19 0.84 0.71 0.29 1
## satisfying 28 0.82 0.68 0.32 1
## nice 22 0.81 0.66 0.34 1
## tasteful 30 0.81 0.65 0.35 1
## pleasing 24 0.80 0.65 0.35 1
## delightful 10 0.79 0.62 0.38 1
## inviting 18 0.78 0.61 0.39 1
## pretty 25 0.76 0.58 0.42 1
## beautiful 5 0.76 0.57 0.43 1
## motivating 21 0.75 0.56 0.44 1
## lovely 20 0.74 0.54 0.46 1
## engaging 12 0.74 0.54 0.46 1
## wellDesigned 31 0.73 0.53 0.47 1
## fascinating 15 0.72 0.51 0.49 1
## elegant 11 0.71 0.50 0.50 1
## exciting 14 0.70 0.49 0.51 1
## harmonious 16 0.69 0.48 0.52 1
## sophisticated 29 0.66 0.43 0.57 1
## balanced 4 0.65 0.42 0.58 1
## creative 9 0.62 0.39 0.61 1
## interesting 17 0.61 0.37 0.63 1
## clean 6 0.60 0.36 0.64 1
## organized 23 0.59 0.35 0.65 1
## artistic 2 0.56 0.32 0.68 1
## professional 26 0.50 0.25 0.75 1
## colorHarmonious 8 0.43 0.19 0.81 1
## cluttered 7 0.41 0.17 0.83 1
## provoking 27 0.32 0.10 0.90 1
##
## PA1
## SS loadings 15.38
## Proportion Var 0.50
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 434 and the objective function was 6.37
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## attractive 3 0.75 0.42 0.74 0.26 1.6
## pretty 25 0.75 0.30 0.65 0.35 1.3
## artistic 2 0.74 0.01 0.54 0.46 1.0
## creative 9 0.70 0.14 0.51 0.49 1.1
## beautiful 5 0.69 0.36 0.60 0.40 1.5
## fascinating 15 0.69 0.30 0.56 0.44 1.4
## enjoyable 13 0.68 0.50 0.71 0.29 1.8
## exciting 14 0.68 0.28 0.54 0.46 1.3
## appealing 1 0.67 0.52 0.72 0.28 1.9
## delightful 10 0.67 0.43 0.63 0.37 1.7
## likable 19 0.67 0.51 0.71 0.29 1.9
## lovely 20 0.65 0.38 0.56 0.44 1.6
## inviting 18 0.64 0.45 0.62 0.38 1.8
## nice 22 0.64 0.50 0.66 0.34 1.9
## engaging 12 0.63 0.40 0.55 0.45 1.7
## motivating 21 0.62 0.43 0.57 0.43 1.8
## pleasing 24 0.58 0.55 0.65 0.35 2.0
## interesting 17 0.57 0.26 0.40 0.60 1.4
## provoking 27 0.35 0.08 0.13 0.87 1.1
## clean 6 0.14 0.78 0.63 0.37 1.1
## professional 26 0.05 0.73 0.54 0.46 1.0
## organized 23 0.18 0.71 0.53 0.47 1.1
## wellDesigned 31 0.38 0.68 0.61 0.39 1.6
## balanced 4 0.29 0.67 0.53 0.47 1.4
## harmonious 16 0.37 0.64 0.55 0.45 1.6
## satisfying 28 0.56 0.61 0.69 0.31 2.0
## tasteful 30 0.54 0.61 0.66 0.34 2.0
## elegant 11 0.44 0.58 0.53 0.47 1.9
## sophisticated 29 0.40 0.55 0.46 0.54 1.8
## cluttered 7 0.22 0.37 0.18 0.82 1.6
## colorHarmonious 8 0.30 0.32 0.19 0.81 2.0
##
## PA1 PA2
## SS loadings 9.70 7.45
## Proportion Var 0.31 0.24
## Cumulative Var 0.31 0.55
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.81 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.97 -0.40 0.54 0.46 1.3
## creative 9 0.85 -0.20 0.51 0.49 1.1
## pretty 25 0.82 -0.03 0.65 0.35 1.0
## attractive 3 0.76 0.13 0.74 0.26 1.1
## exciting 14 0.75 -0.02 0.54 0.46 1.0
## fascinating 15 0.74 0.01 0.56 0.44 1.0
## beautiful 5 0.71 0.09 0.60 0.40 1.0
## delightful 10 0.64 0.20 0.63 0.37 1.2
## lovely 20 0.64 0.14 0.56 0.44 1.1
## enjoyable 13 0.62 0.28 0.71 0.29 1.4
## interesting 17 0.61 0.03 0.40 0.60 1.0
## engaging 12 0.61 0.18 0.55 0.45 1.2
## inviting 18 0.60 0.23 0.62 0.38 1.3
## likable 19 0.60 0.30 0.71 0.29 1.5
## appealing 1 0.59 0.31 0.72 0.28 1.5
## motivating 21 0.58 0.22 0.57 0.43 1.3
## nice 22 0.57 0.30 0.66 0.34 1.5
## pleasing 24 0.47 0.40 0.65 0.35 2.0
## provoking 27 0.42 -0.10 0.13 0.87 1.1
## clean 6 -0.25 0.95 0.63 0.37 1.1
## professional 26 -0.34 0.94 0.54 0.46 1.3
## organized 23 -0.15 0.83 0.53 0.47 1.1
## balanced 4 0.01 0.72 0.53 0.47 1.0
## wellDesigned 31 0.12 0.69 0.61 0.39 1.1
## harmonious 16 0.13 0.64 0.55 0.45 1.1
## elegant 11 0.26 0.52 0.53 0.47 1.5
## sophisticated 29 0.22 0.50 0.46 0.54 1.4
## tasteful 30 0.38 0.50 0.66 0.34 1.9
## satisfying 28 0.40 0.49 0.69 0.31 1.9
## cluttered 7 0.09 0.36 0.18 0.82 1.1
## colorHarmonious 8 0.21 0.26 0.19 0.81 1.9
##
## PA1 PA2
## SS loadings 10.21 6.94
## Proportion Var 0.33 0.22
## Cumulative Var 0.33 0.55
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.85 0.72 0.28 1
## attractive 3 0.84 0.71 0.29 1
## enjoyable 13 0.84 0.71 0.29 1
## likable 19 0.84 0.71 0.29 1
## satisfying 28 0.82 0.68 0.32 1
## nice 22 0.81 0.66 0.34 1
## tasteful 30 0.81 0.65 0.35 1
## pleasing 24 0.80 0.65 0.35 1
## delightful 10 0.79 0.62 0.38 1
## inviting 18 0.78 0.61 0.39 1
## pretty 25 0.76 0.58 0.42 1
## beautiful 5 0.76 0.57 0.43 1
## motivating 21 0.75 0.56 0.44 1
## lovely 20 0.74 0.54 0.46 1
## engaging 12 0.74 0.54 0.46 1
## wellDesigned 31 0.73 0.53 0.47 1
## fascinating 15 0.72 0.51 0.49 1
## elegant 11 0.71 0.50 0.50 1
## exciting 14 0.70 0.49 0.51 1
## harmonious 16 0.69 0.48 0.52 1
## sophisticated 29 0.66 0.43 0.57 1
## balanced 4 0.65 0.42 0.58 1
## creative 9 0.62 0.39 0.61 1
## interesting 17 0.61 0.37 0.63 1
## clean 6 0.60 0.36 0.64 1
## organized 23 0.59 0.35 0.65 1
## artistic 2 0.56 0.32 0.68 1
## professional 26 0.50 0.25 0.75 1
## colorHarmonious 8 0.43 0.19 0.81 1
## cluttered 7 0.41 0.17 0.83 1
## provoking 27 0.32 0.10 0.90 1
##
## PA1
## SS loadings 15.38
## Proportion Var 0.50
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 434 and the objective function was 6.37
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## attractive 3 0.75 0.42 0.74 0.26 1.6
## pretty 25 0.75 0.30 0.65 0.35 1.3
## artistic 2 0.74 0.01 0.54 0.46 1.0
## creative 9 0.70 0.14 0.51 0.49 1.1
## beautiful 5 0.69 0.36 0.60 0.40 1.5
## fascinating 15 0.69 0.30 0.56 0.44 1.4
## enjoyable 13 0.68 0.50 0.71 0.29 1.8
## exciting 14 0.68 0.28 0.54 0.46 1.3
## appealing 1 0.67 0.52 0.72 0.28 1.9
## delightful 10 0.67 0.43 0.63 0.37 1.7
## likable 19 0.67 0.51 0.71 0.29 1.9
## lovely 20 0.65 0.38 0.56 0.44 1.6
## inviting 18 0.64 0.45 0.62 0.38 1.8
## nice 22 0.64 0.50 0.66 0.34 1.9
## engaging 12 0.63 0.40 0.55 0.45 1.7
## motivating 21 0.62 0.43 0.57 0.43 1.8
## pleasing 24 0.58 0.55 0.65 0.35 2.0
## interesting 17 0.57 0.26 0.40 0.60 1.4
## provoking 27 0.35 0.08 0.13 0.87 1.1
## clean 6 0.14 0.78 0.63 0.37 1.1
## professional 26 0.05 0.73 0.54 0.46 1.0
## organized 23 0.18 0.71 0.53 0.47 1.1
## wellDesigned 31 0.38 0.68 0.61 0.39 1.6
## balanced 4 0.29 0.67 0.53 0.47 1.4
## harmonious 16 0.37 0.64 0.55 0.45 1.6
## satisfying 28 0.56 0.61 0.69 0.31 2.0
## tasteful 30 0.54 0.61 0.66 0.34 2.0
## elegant 11 0.44 0.58 0.53 0.47 1.9
## sophisticated 29 0.40 0.55 0.46 0.54 1.8
## cluttered 7 0.22 0.37 0.18 0.82 1.6
## colorHarmonious 8 0.30 0.32 0.19 0.81 2.0
##
## PA1 PA2
## SS loadings 9.70 7.45
## Proportion Var 0.31 0.24
## Cumulative Var 0.31 0.55
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.81 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.97 -0.40 0.54 0.46 1.3
## creative 9 0.85 -0.20 0.51 0.49 1.1
## pretty 25 0.82 -0.03 0.65 0.35 1.0
## attractive 3 0.76 0.13 0.74 0.26 1.1
## exciting 14 0.75 -0.02 0.54 0.46 1.0
## fascinating 15 0.74 0.01 0.56 0.44 1.0
## beautiful 5 0.71 0.09 0.60 0.40 1.0
## delightful 10 0.64 0.20 0.63 0.37 1.2
## lovely 20 0.64 0.14 0.56 0.44 1.1
## enjoyable 13 0.62 0.28 0.71 0.29 1.4
## interesting 17 0.61 0.03 0.40 0.60 1.0
## engaging 12 0.61 0.18 0.55 0.45 1.2
## inviting 18 0.60 0.23 0.62 0.38 1.3
## likable 19 0.60 0.30 0.71 0.29 1.5
## appealing 1 0.59 0.31 0.72 0.28 1.5
## motivating 21 0.58 0.22 0.57 0.43 1.3
## nice 22 0.57 0.30 0.66 0.34 1.5
## pleasing 24 0.47 0.40 0.65 0.35 2.0
## provoking 27 0.42 -0.10 0.13 0.87 1.1
## clean 6 -0.25 0.95 0.63 0.37 1.1
## professional 26 -0.34 0.94 0.54 0.46 1.3
## organized 23 -0.15 0.83 0.53 0.47 1.1
## balanced 4 0.01 0.72 0.53 0.47 1.0
## wellDesigned 31 0.12 0.69 0.61 0.39 1.1
## harmonious 16 0.13 0.64 0.55 0.45 1.1
## elegant 11 0.26 0.52 0.53 0.47 1.5
## sophisticated 29 0.22 0.50 0.46 0.54 1.4
## tasteful 30 0.38 0.50 0.66 0.34 1.9
## satisfying 28 0.40 0.49 0.69 0.31 1.9
## cluttered 7 0.09 0.36 0.18 0.82 1.1
## colorHarmonious 8 0.21 0.26 0.19 0.81 1.9
##
## PA1 PA2
## SS loadings 10.21 6.94
## Proportion Var 0.33 0.22
## Cumulative Var 0.33 0.55
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.85 0.72 0.28 1
## attractive 3 0.84 0.71 0.29 1
## enjoyable 13 0.84 0.71 0.29 1
## likable 19 0.84 0.71 0.29 1
## satisfying 28 0.82 0.68 0.32 1
## nice 22 0.81 0.66 0.34 1
## tasteful 30 0.81 0.65 0.35 1
## pleasing 24 0.80 0.65 0.35 1
## delightful 10 0.79 0.62 0.38 1
## inviting 18 0.78 0.61 0.39 1
## pretty 25 0.76 0.58 0.42 1
## beautiful 5 0.76 0.57 0.43 1
## motivating 21 0.75 0.56 0.44 1
## lovely 20 0.74 0.54 0.46 1
## engaging 12 0.74 0.54 0.46 1
## wellDesigned 31 0.73 0.53 0.47 1
## fascinating 15 0.72 0.51 0.49 1
## elegant 11 0.71 0.50 0.50 1
## exciting 14 0.70 0.49 0.51 1
## harmonious 16 0.69 0.48 0.52 1
## sophisticated 29 0.66 0.43 0.57 1
## balanced 4 0.65 0.42 0.58 1
## creative 9 0.62 0.39 0.61 1
## interesting 17 0.61 0.37 0.63 1
## clean 6 0.60 0.36 0.64 1
## organized 23 0.59 0.35 0.65 1
## artistic 2 0.56 0.32 0.68 1
## professional 26 0.50 0.25 0.75 1
## colorHarmonious 8 0.43 0.19 0.81 1
## cluttered 7 0.41 0.17 0.83 1
## provoking 27 0.32 0.10 0.90 1
##
## PA1
## SS loadings 15.38
## Proportion Var 0.50
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 434 and the objective function was 6.37
##
## The root mean square of the residuals (RMSR) is 0.07
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.97
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## attractive 3 0.75 0.42 0.74 0.26 1.6
## pretty 25 0.75 0.30 0.65 0.35 1.3
## artistic 2 0.74 0.01 0.54 0.46 1.0
## creative 9 0.70 0.14 0.51 0.49 1.1
## beautiful 5 0.69 0.36 0.60 0.40 1.5
## fascinating 15 0.69 0.30 0.56 0.44 1.4
## enjoyable 13 0.68 0.50 0.71 0.29 1.8
## exciting 14 0.68 0.28 0.54 0.46 1.3
## appealing 1 0.67 0.52 0.72 0.28 1.9
## delightful 10 0.67 0.43 0.63 0.37 1.7
## likable 19 0.67 0.51 0.71 0.29 1.9
## lovely 20 0.65 0.38 0.56 0.44 1.6
## inviting 18 0.64 0.45 0.62 0.38 1.8
## nice 22 0.64 0.50 0.66 0.34 1.9
## engaging 12 0.63 0.40 0.55 0.45 1.7
## motivating 21 0.62 0.43 0.57 0.43 1.8
## pleasing 24 0.58 0.55 0.65 0.35 2.0
## interesting 17 0.57 0.26 0.40 0.60 1.4
## provoking 27 0.35 0.08 0.13 0.87 1.1
## clean 6 0.14 0.78 0.63 0.37 1.1
## professional 26 0.05 0.73 0.54 0.46 1.0
## organized 23 0.18 0.71 0.53 0.47 1.1
## wellDesigned 31 0.38 0.68 0.61 0.39 1.6
## balanced 4 0.29 0.67 0.53 0.47 1.4
## harmonious 16 0.37 0.64 0.55 0.45 1.6
## satisfying 28 0.56 0.61 0.69 0.31 2.0
## tasteful 30 0.54 0.61 0.66 0.34 2.0
## elegant 11 0.44 0.58 0.53 0.47 1.9
## sophisticated 29 0.40 0.55 0.46 0.54 1.8
## cluttered 7 0.22 0.37 0.18 0.82 1.6
## colorHarmonious 8 0.30 0.32 0.19 0.81 2.0
##
## PA1 PA2
## SS loadings 9.70 7.45
## Proportion Var 0.31 0.24
## Cumulative Var 0.31 0.55
## Proportion Explained 0.57 0.43
## Cumulative Proportion 0.57 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.81 0.74
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.97 -0.40 0.54 0.46 1.3
## creative 9 0.85 -0.20 0.51 0.49 1.1
## pretty 25 0.82 -0.03 0.65 0.35 1.0
## attractive 3 0.76 0.13 0.74 0.26 1.1
## exciting 14 0.75 -0.02 0.54 0.46 1.0
## fascinating 15 0.74 0.01 0.56 0.44 1.0
## beautiful 5 0.71 0.09 0.60 0.40 1.0
## delightful 10 0.64 0.20 0.63 0.37 1.2
## lovely 20 0.64 0.14 0.56 0.44 1.1
## enjoyable 13 0.62 0.28 0.71 0.29 1.4
## interesting 17 0.61 0.03 0.40 0.60 1.0
## engaging 12 0.61 0.18 0.55 0.45 1.2
## inviting 18 0.60 0.23 0.62 0.38 1.3
## likable 19 0.60 0.30 0.71 0.29 1.5
## appealing 1 0.59 0.31 0.72 0.28 1.5
## motivating 21 0.58 0.22 0.57 0.43 1.3
## nice 22 0.57 0.30 0.66 0.34 1.5
## pleasing 24 0.47 0.40 0.65 0.35 2.0
## provoking 27 0.42 -0.10 0.13 0.87 1.1
## clean 6 -0.25 0.95 0.63 0.37 1.1
## professional 26 -0.34 0.94 0.54 0.46 1.3
## organized 23 -0.15 0.83 0.53 0.47 1.1
## balanced 4 0.01 0.72 0.53 0.47 1.0
## wellDesigned 31 0.12 0.69 0.61 0.39 1.1
## harmonious 16 0.13 0.64 0.55 0.45 1.1
## elegant 11 0.26 0.52 0.53 0.47 1.5
## sophisticated 29 0.22 0.50 0.46 0.54 1.4
## tasteful 30 0.38 0.50 0.66 0.34 1.9
## satisfying 28 0.40 0.49 0.69 0.31 1.9
## cluttered 7 0.09 0.36 0.18 0.82 1.1
## colorHarmonious 8 0.21 0.26 0.19 0.81 1.9
##
## PA1 PA2
## SS loadings 10.21 6.94
## Proportion Var 0.33 0.22
## Cumulative Var 0.33 0.55
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.72
## PA2 0.72 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 25.71
## The degrees of freedom for the model are 404 and the objective function was 4.59
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.05
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.94
## Minimum correlation of possible factor scores 0.92 0.88
##
##
## ## Image 10
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.88 0.772 0.23 1
## pleasing 24 0.88 0.770 0.23 1
## enjoyable 13 0.87 0.755 0.25 1
## likable 19 0.86 0.736 0.26 1
## attractive 3 0.86 0.733 0.27 1
## nice 22 0.85 0.718 0.28 1
## satisfying 28 0.85 0.717 0.28 1
## elegant 11 0.84 0.707 0.29 1
## beautiful 5 0.82 0.678 0.32 1
## delightful 10 0.82 0.670 0.33 1
## lovely 20 0.81 0.661 0.34 1
## tasteful 30 0.80 0.642 0.36 1
## pretty 25 0.80 0.642 0.36 1
## harmonious 16 0.80 0.638 0.36 1
## inviting 18 0.78 0.613 0.39 1
## balanced 4 0.77 0.599 0.40 1
## motivating 21 0.77 0.595 0.40 1
## exciting 14 0.77 0.586 0.41 1
## engaging 12 0.76 0.578 0.42 1
## wellDesigned 31 0.74 0.546 0.45 1
## creative 9 0.68 0.464 0.54 1
## clean 6 0.68 0.458 0.54 1
## artistic 2 0.66 0.439 0.56 1
## fascinating 15 0.66 0.436 0.56 1
## organized 23 0.66 0.433 0.57 1
## interesting 17 0.64 0.412 0.59 1
## sophisticated 29 0.63 0.395 0.61 1
## colorHarmonious 8 0.62 0.379 0.62 1
## professional 26 0.61 0.375 0.62 1
## cluttered 7 0.45 0.199 0.80 1
## provoking 27 0.27 0.075 0.92 1
##
## PA1
## SS loadings 17.42
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 434 and the objective function was 5.16
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.78 0.13 0.62 0.38 1.1
## clean 6 0.75 0.19 0.60 0.40 1.1
## wellDesigned 31 0.74 0.29 0.63 0.37 1.3
## balanced 4 0.72 0.36 0.65 0.35 1.5
## inviting 18 0.68 0.41 0.64 0.36 1.6
## elegant 11 0.68 0.51 0.71 0.29 1.9
## harmonious 16 0.67 0.45 0.65 0.35 1.8
## nice 22 0.66 0.54 0.72 0.28 1.9
## lovely 20 0.65 0.50 0.66 0.34 1.9
## pleasing 24 0.63 0.61 0.77 0.23 2.0
## tasteful 30 0.62 0.51 0.64 0.36 1.9
## professional 26 0.62 0.24 0.43 0.57 1.3
## delightful 10 0.61 0.54 0.67 0.33 2.0
## motivating 21 0.60 0.49 0.60 0.40 1.9
## engaging 12 0.55 0.52 0.58 0.42 2.0
## sophisticated 29 0.54 0.34 0.41 0.59 1.7
## colorHarmonious 8 0.50 0.36 0.38 0.62 1.8
## cluttered 7 0.47 0.15 0.24 0.76 1.2
## artistic 2 0.24 0.72 0.59 0.41 1.2
## exciting 14 0.40 0.70 0.65 0.35 1.6
## pretty 25 0.47 0.68 0.68 0.32 1.8
## appealing 1 0.57 0.68 0.79 0.21 1.9
## attractive 3 0.55 0.67 0.75 0.25 1.9
## creative 9 0.32 0.67 0.54 0.46 1.4
## enjoyable 13 0.57 0.66 0.76 0.24 2.0
## beautiful 5 0.54 0.63 0.69 0.31 1.9
## fascinating 15 0.32 0.63 0.50 0.50 1.5
## interesting 17 0.31 0.62 0.48 0.52 1.5
## likable 19 0.60 0.61 0.74 0.26 2.0
## satisfying 28 0.60 0.60 0.72 0.28 2.0
## provoking 27 0.00 0.41 0.17 0.83 1.0
##
## PA1 PA2
## SS loadings 10.13 8.53
## Proportion Var 0.33 0.28
## Cumulative Var 0.33 0.60
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.93 0.92
## Multiple R square of scores with factors 0.87 0.85
## Minimum correlation of possible factor scores 0.75 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.99 -0.31 0.62 0.38 1.2
## clean 6 0.92 -0.21 0.60 0.40 1.1
## wellDesigned 31 0.85 -0.07 0.63 0.37 1.0
## balanced 4 0.77 0.04 0.65 0.35 1.0
## professional 26 0.70 -0.06 0.43 0.57 1.0
## inviting 18 0.68 0.14 0.64 0.36 1.1
## harmonious 16 0.64 0.20 0.65 0.35 1.2
## elegant 11 0.62 0.28 0.71 0.29 1.4
## lovely 20 0.58 0.28 0.66 0.34 1.4
## nice 22 0.57 0.33 0.72 0.28 1.6
## cluttered 7 0.55 -0.09 0.24 0.76 1.1
## tasteful 30 0.54 0.31 0.64 0.36 1.6
## sophisticated 29 0.54 0.13 0.41 0.59 1.1
## motivating 21 0.52 0.30 0.60 0.40 1.6
## delightful 10 0.51 0.36 0.67 0.33 1.8
## pleasing 24 0.49 0.44 0.77 0.23 2.0
## colorHarmonious 8 0.46 0.19 0.38 0.62 1.3
## engaging 12 0.43 0.38 0.58 0.42 2.0
## artistic 2 -0.12 0.85 0.59 0.41 1.0
## creative 9 0.02 0.72 0.54 0.46 1.0
## exciting 14 0.11 0.72 0.65 0.35 1.0
## fascinating 15 0.05 0.67 0.50 0.50 1.0
## interesting 17 0.03 0.67 0.48 0.52 1.0
## pretty 25 0.22 0.65 0.68 0.32 1.2
## appealing 1 0.36 0.58 0.79 0.21 1.7
## provoking 27 -0.27 0.58 0.17 0.83 1.4
## attractive 3 0.34 0.58 0.75 0.25 1.6
## enjoyable 13 0.38 0.55 0.76 0.24 1.8
## beautiful 5 0.34 0.54 0.69 0.31 1.7
## likable 19 0.45 0.47 0.74 0.26 2.0
## satisfying 28 0.44 0.46 0.72 0.28 2.0
##
## PA1 PA2
## SS loadings 10.52 8.14
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.95
## Minimum correlation of possible factor scores 0.92 0.89
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.88 0.772 0.23 1
## pleasing 24 0.88 0.770 0.23 1
## enjoyable 13 0.87 0.755 0.25 1
## likable 19 0.86 0.736 0.26 1
## attractive 3 0.86 0.733 0.27 1
## nice 22 0.85 0.718 0.28 1
## satisfying 28 0.85 0.717 0.28 1
## elegant 11 0.84 0.707 0.29 1
## beautiful 5 0.82 0.678 0.32 1
## delightful 10 0.82 0.670 0.33 1
## lovely 20 0.81 0.661 0.34 1
## tasteful 30 0.80 0.642 0.36 1
## pretty 25 0.80 0.642 0.36 1
## harmonious 16 0.80 0.638 0.36 1
## inviting 18 0.78 0.613 0.39 1
## balanced 4 0.77 0.599 0.40 1
## motivating 21 0.77 0.595 0.40 1
## exciting 14 0.77 0.586 0.41 1
## engaging 12 0.76 0.578 0.42 1
## wellDesigned 31 0.74 0.546 0.45 1
## creative 9 0.68 0.464 0.54 1
## clean 6 0.68 0.458 0.54 1
## artistic 2 0.66 0.439 0.56 1
## fascinating 15 0.66 0.436 0.56 1
## organized 23 0.66 0.433 0.57 1
## interesting 17 0.64 0.412 0.59 1
## sophisticated 29 0.63 0.395 0.61 1
## colorHarmonious 8 0.62 0.379 0.62 1
## professional 26 0.61 0.375 0.62 1
## cluttered 7 0.45 0.199 0.80 1
## provoking 27 0.27 0.075 0.92 1
##
## PA1
## SS loadings 17.42
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 434 and the objective function was 5.16
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.78 0.13 0.62 0.38 1.1
## clean 6 0.75 0.19 0.60 0.40 1.1
## wellDesigned 31 0.74 0.29 0.63 0.37 1.3
## balanced 4 0.72 0.36 0.65 0.35 1.5
## inviting 18 0.68 0.41 0.64 0.36 1.6
## elegant 11 0.68 0.51 0.71 0.29 1.9
## harmonious 16 0.67 0.45 0.65 0.35 1.8
## nice 22 0.66 0.54 0.72 0.28 1.9
## lovely 20 0.65 0.50 0.66 0.34 1.9
## pleasing 24 0.63 0.61 0.77 0.23 2.0
## tasteful 30 0.62 0.51 0.64 0.36 1.9
## professional 26 0.62 0.24 0.43 0.57 1.3
## delightful 10 0.61 0.54 0.67 0.33 2.0
## motivating 21 0.60 0.49 0.60 0.40 1.9
## engaging 12 0.55 0.52 0.58 0.42 2.0
## sophisticated 29 0.54 0.34 0.41 0.59 1.7
## colorHarmonious 8 0.50 0.36 0.38 0.62 1.8
## cluttered 7 0.47 0.15 0.24 0.76 1.2
## artistic 2 0.24 0.72 0.59 0.41 1.2
## exciting 14 0.40 0.70 0.65 0.35 1.6
## pretty 25 0.47 0.68 0.68 0.32 1.8
## appealing 1 0.57 0.68 0.79 0.21 1.9
## attractive 3 0.55 0.67 0.75 0.25 1.9
## creative 9 0.32 0.67 0.54 0.46 1.4
## enjoyable 13 0.57 0.66 0.76 0.24 2.0
## beautiful 5 0.54 0.63 0.69 0.31 1.9
## fascinating 15 0.32 0.63 0.50 0.50 1.5
## interesting 17 0.31 0.62 0.48 0.52 1.5
## likable 19 0.60 0.61 0.74 0.26 2.0
## satisfying 28 0.60 0.60 0.72 0.28 2.0
## provoking 27 0.00 0.41 0.17 0.83 1.0
##
## PA1 PA2
## SS loadings 10.13 8.53
## Proportion Var 0.33 0.28
## Cumulative Var 0.33 0.60
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.93 0.92
## Multiple R square of scores with factors 0.87 0.85
## Minimum correlation of possible factor scores 0.75 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.99 -0.31 0.62 0.38 1.2
## clean 6 0.92 -0.21 0.60 0.40 1.1
## wellDesigned 31 0.85 -0.07 0.63 0.37 1.0
## balanced 4 0.77 0.04 0.65 0.35 1.0
## professional 26 0.70 -0.06 0.43 0.57 1.0
## inviting 18 0.68 0.14 0.64 0.36 1.1
## harmonious 16 0.64 0.20 0.65 0.35 1.2
## elegant 11 0.62 0.28 0.71 0.29 1.4
## lovely 20 0.58 0.28 0.66 0.34 1.4
## nice 22 0.57 0.33 0.72 0.28 1.6
## cluttered 7 0.55 -0.09 0.24 0.76 1.1
## tasteful 30 0.54 0.31 0.64 0.36 1.6
## sophisticated 29 0.54 0.13 0.41 0.59 1.1
## motivating 21 0.52 0.30 0.60 0.40 1.6
## delightful 10 0.51 0.36 0.67 0.33 1.8
## pleasing 24 0.49 0.44 0.77 0.23 2.0
## colorHarmonious 8 0.46 0.19 0.38 0.62 1.3
## engaging 12 0.43 0.38 0.58 0.42 2.0
## artistic 2 -0.12 0.85 0.59 0.41 1.0
## creative 9 0.02 0.72 0.54 0.46 1.0
## exciting 14 0.11 0.72 0.65 0.35 1.0
## fascinating 15 0.05 0.67 0.50 0.50 1.0
## interesting 17 0.03 0.67 0.48 0.52 1.0
## pretty 25 0.22 0.65 0.68 0.32 1.2
## appealing 1 0.36 0.58 0.79 0.21 1.7
## provoking 27 -0.27 0.58 0.17 0.83 1.4
## attractive 3 0.34 0.58 0.75 0.25 1.6
## enjoyable 13 0.38 0.55 0.76 0.24 1.8
## beautiful 5 0.34 0.54 0.69 0.31 1.7
## likable 19 0.45 0.47 0.74 0.26 2.0
## satisfying 28 0.44 0.46 0.72 0.28 2.0
##
## PA1 PA2
## SS loadings 10.52 8.14
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.95
## Minimum correlation of possible factor scores 0.92 0.89
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.88 0.772 0.23 1
## pleasing 24 0.88 0.770 0.23 1
## enjoyable 13 0.87 0.755 0.25 1
## likable 19 0.86 0.736 0.26 1
## attractive 3 0.86 0.733 0.27 1
## nice 22 0.85 0.718 0.28 1
## satisfying 28 0.85 0.717 0.28 1
## elegant 11 0.84 0.707 0.29 1
## beautiful 5 0.82 0.678 0.32 1
## delightful 10 0.82 0.670 0.33 1
## lovely 20 0.81 0.661 0.34 1
## tasteful 30 0.80 0.642 0.36 1
## pretty 25 0.80 0.642 0.36 1
## harmonious 16 0.80 0.638 0.36 1
## inviting 18 0.78 0.613 0.39 1
## balanced 4 0.77 0.599 0.40 1
## motivating 21 0.77 0.595 0.40 1
## exciting 14 0.77 0.586 0.41 1
## engaging 12 0.76 0.578 0.42 1
## wellDesigned 31 0.74 0.546 0.45 1
## creative 9 0.68 0.464 0.54 1
## clean 6 0.68 0.458 0.54 1
## artistic 2 0.66 0.439 0.56 1
## fascinating 15 0.66 0.436 0.56 1
## organized 23 0.66 0.433 0.57 1
## interesting 17 0.64 0.412 0.59 1
## sophisticated 29 0.63 0.395 0.61 1
## colorHarmonious 8 0.62 0.379 0.62 1
## professional 26 0.61 0.375 0.62 1
## cluttered 7 0.45 0.199 0.80 1
## provoking 27 0.27 0.075 0.92 1
##
## PA1
## SS loadings 17.42
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 434 and the objective function was 5.16
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.78 0.13 0.62 0.38 1.1
## clean 6 0.75 0.19 0.60 0.40 1.1
## wellDesigned 31 0.74 0.29 0.63 0.37 1.3
## balanced 4 0.72 0.36 0.65 0.35 1.5
## inviting 18 0.68 0.41 0.64 0.36 1.6
## elegant 11 0.68 0.51 0.71 0.29 1.9
## harmonious 16 0.67 0.45 0.65 0.35 1.8
## nice 22 0.66 0.54 0.72 0.28 1.9
## lovely 20 0.65 0.50 0.66 0.34 1.9
## pleasing 24 0.63 0.61 0.77 0.23 2.0
## tasteful 30 0.62 0.51 0.64 0.36 1.9
## professional 26 0.62 0.24 0.43 0.57 1.3
## delightful 10 0.61 0.54 0.67 0.33 2.0
## motivating 21 0.60 0.49 0.60 0.40 1.9
## engaging 12 0.55 0.52 0.58 0.42 2.0
## sophisticated 29 0.54 0.34 0.41 0.59 1.7
## colorHarmonious 8 0.50 0.36 0.38 0.62 1.8
## cluttered 7 0.47 0.15 0.24 0.76 1.2
## artistic 2 0.24 0.72 0.59 0.41 1.2
## exciting 14 0.40 0.70 0.65 0.35 1.6
## pretty 25 0.47 0.68 0.68 0.32 1.8
## appealing 1 0.57 0.68 0.79 0.21 1.9
## attractive 3 0.55 0.67 0.75 0.25 1.9
## creative 9 0.32 0.67 0.54 0.46 1.4
## enjoyable 13 0.57 0.66 0.76 0.24 2.0
## beautiful 5 0.54 0.63 0.69 0.31 1.9
## fascinating 15 0.32 0.63 0.50 0.50 1.5
## interesting 17 0.31 0.62 0.48 0.52 1.5
## likable 19 0.60 0.61 0.74 0.26 2.0
## satisfying 28 0.60 0.60 0.72 0.28 2.0
## provoking 27 0.00 0.41 0.17 0.83 1.0
##
## PA1 PA2
## SS loadings 10.13 8.53
## Proportion Var 0.33 0.28
## Cumulative Var 0.33 0.60
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.93 0.92
## Multiple R square of scores with factors 0.87 0.85
## Minimum correlation of possible factor scores 0.75 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.99 -0.31 0.62 0.38 1.2
## clean 6 0.92 -0.21 0.60 0.40 1.1
## wellDesigned 31 0.85 -0.07 0.63 0.37 1.0
## balanced 4 0.77 0.04 0.65 0.35 1.0
## professional 26 0.70 -0.06 0.43 0.57 1.0
## inviting 18 0.68 0.14 0.64 0.36 1.1
## harmonious 16 0.64 0.20 0.65 0.35 1.2
## elegant 11 0.62 0.28 0.71 0.29 1.4
## lovely 20 0.58 0.28 0.66 0.34 1.4
## nice 22 0.57 0.33 0.72 0.28 1.6
## cluttered 7 0.55 -0.09 0.24 0.76 1.1
## tasteful 30 0.54 0.31 0.64 0.36 1.6
## sophisticated 29 0.54 0.13 0.41 0.59 1.1
## motivating 21 0.52 0.30 0.60 0.40 1.6
## delightful 10 0.51 0.36 0.67 0.33 1.8
## pleasing 24 0.49 0.44 0.77 0.23 2.0
## colorHarmonious 8 0.46 0.19 0.38 0.62 1.3
## engaging 12 0.43 0.38 0.58 0.42 2.0
## artistic 2 -0.12 0.85 0.59 0.41 1.0
## creative 9 0.02 0.72 0.54 0.46 1.0
## exciting 14 0.11 0.72 0.65 0.35 1.0
## fascinating 15 0.05 0.67 0.50 0.50 1.0
## interesting 17 0.03 0.67 0.48 0.52 1.0
## pretty 25 0.22 0.65 0.68 0.32 1.2
## appealing 1 0.36 0.58 0.79 0.21 1.7
## provoking 27 -0.27 0.58 0.17 0.83 1.4
## attractive 3 0.34 0.58 0.75 0.25 1.6
## enjoyable 13 0.38 0.55 0.76 0.24 1.8
## beautiful 5 0.34 0.54 0.69 0.31 1.7
## likable 19 0.45 0.47 0.74 0.26 2.0
## satisfying 28 0.44 0.46 0.72 0.28 2.0
##
## PA1 PA2
## SS loadings 10.52 8.14
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.95
## Minimum correlation of possible factor scores 0.92 0.89
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.88 0.772 0.23 1
## pleasing 24 0.88 0.770 0.23 1
## enjoyable 13 0.87 0.755 0.25 1
## likable 19 0.86 0.736 0.26 1
## attractive 3 0.86 0.733 0.27 1
## nice 22 0.85 0.718 0.28 1
## satisfying 28 0.85 0.717 0.28 1
## elegant 11 0.84 0.707 0.29 1
## beautiful 5 0.82 0.678 0.32 1
## delightful 10 0.82 0.670 0.33 1
## lovely 20 0.81 0.661 0.34 1
## tasteful 30 0.80 0.642 0.36 1
## pretty 25 0.80 0.642 0.36 1
## harmonious 16 0.80 0.638 0.36 1
## inviting 18 0.78 0.613 0.39 1
## balanced 4 0.77 0.599 0.40 1
## motivating 21 0.77 0.595 0.40 1
## exciting 14 0.77 0.586 0.41 1
## engaging 12 0.76 0.578 0.42 1
## wellDesigned 31 0.74 0.546 0.45 1
## creative 9 0.68 0.464 0.54 1
## clean 6 0.68 0.458 0.54 1
## artistic 2 0.66 0.439 0.56 1
## fascinating 15 0.66 0.436 0.56 1
## organized 23 0.66 0.433 0.57 1
## interesting 17 0.64 0.412 0.59 1
## sophisticated 29 0.63 0.395 0.61 1
## colorHarmonious 8 0.62 0.379 0.62 1
## professional 26 0.61 0.375 0.62 1
## cluttered 7 0.45 0.199 0.80 1
## provoking 27 0.27 0.075 0.92 1
##
## PA1
## SS loadings 17.42
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 434 and the objective function was 5.16
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.78 0.13 0.62 0.38 1.1
## clean 6 0.75 0.19 0.60 0.40 1.1
## wellDesigned 31 0.74 0.29 0.63 0.37 1.3
## balanced 4 0.72 0.36 0.65 0.35 1.5
## inviting 18 0.68 0.41 0.64 0.36 1.6
## elegant 11 0.68 0.51 0.71 0.29 1.9
## harmonious 16 0.67 0.45 0.65 0.35 1.8
## nice 22 0.66 0.54 0.72 0.28 1.9
## lovely 20 0.65 0.50 0.66 0.34 1.9
## pleasing 24 0.63 0.61 0.77 0.23 2.0
## tasteful 30 0.62 0.51 0.64 0.36 1.9
## professional 26 0.62 0.24 0.43 0.57 1.3
## delightful 10 0.61 0.54 0.67 0.33 2.0
## motivating 21 0.60 0.49 0.60 0.40 1.9
## engaging 12 0.55 0.52 0.58 0.42 2.0
## sophisticated 29 0.54 0.34 0.41 0.59 1.7
## colorHarmonious 8 0.50 0.36 0.38 0.62 1.8
## cluttered 7 0.47 0.15 0.24 0.76 1.2
## artistic 2 0.24 0.72 0.59 0.41 1.2
## exciting 14 0.40 0.70 0.65 0.35 1.6
## pretty 25 0.47 0.68 0.68 0.32 1.8
## appealing 1 0.57 0.68 0.79 0.21 1.9
## attractive 3 0.55 0.67 0.75 0.25 1.9
## creative 9 0.32 0.67 0.54 0.46 1.4
## enjoyable 13 0.57 0.66 0.76 0.24 2.0
## beautiful 5 0.54 0.63 0.69 0.31 1.9
## fascinating 15 0.32 0.63 0.50 0.50 1.5
## interesting 17 0.31 0.62 0.48 0.52 1.5
## likable 19 0.60 0.61 0.74 0.26 2.0
## satisfying 28 0.60 0.60 0.72 0.28 2.0
## provoking 27 0.00 0.41 0.17 0.83 1.0
##
## PA1 PA2
## SS loadings 10.13 8.53
## Proportion Var 0.33 0.28
## Cumulative Var 0.33 0.60
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.93 0.92
## Multiple R square of scores with factors 0.87 0.85
## Minimum correlation of possible factor scores 0.75 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.99 -0.31 0.62 0.38 1.2
## clean 6 0.92 -0.21 0.60 0.40 1.1
## wellDesigned 31 0.85 -0.07 0.63 0.37 1.0
## balanced 4 0.77 0.04 0.65 0.35 1.0
## professional 26 0.70 -0.06 0.43 0.57 1.0
## inviting 18 0.68 0.14 0.64 0.36 1.1
## harmonious 16 0.64 0.20 0.65 0.35 1.2
## elegant 11 0.62 0.28 0.71 0.29 1.4
## lovely 20 0.58 0.28 0.66 0.34 1.4
## nice 22 0.57 0.33 0.72 0.28 1.6
## cluttered 7 0.55 -0.09 0.24 0.76 1.1
## tasteful 30 0.54 0.31 0.64 0.36 1.6
## sophisticated 29 0.54 0.13 0.41 0.59 1.1
## motivating 21 0.52 0.30 0.60 0.40 1.6
## delightful 10 0.51 0.36 0.67 0.33 1.8
## pleasing 24 0.49 0.44 0.77 0.23 2.0
## colorHarmonious 8 0.46 0.19 0.38 0.62 1.3
## engaging 12 0.43 0.38 0.58 0.42 2.0
## artistic 2 -0.12 0.85 0.59 0.41 1.0
## creative 9 0.02 0.72 0.54 0.46 1.0
## exciting 14 0.11 0.72 0.65 0.35 1.0
## fascinating 15 0.05 0.67 0.50 0.50 1.0
## interesting 17 0.03 0.67 0.48 0.52 1.0
## pretty 25 0.22 0.65 0.68 0.32 1.2
## appealing 1 0.36 0.58 0.79 0.21 1.7
## provoking 27 -0.27 0.58 0.17 0.83 1.4
## attractive 3 0.34 0.58 0.75 0.25 1.6
## enjoyable 13 0.38 0.55 0.76 0.24 1.8
## beautiful 5 0.34 0.54 0.69 0.31 1.7
## likable 19 0.45 0.47 0.74 0.26 2.0
## satisfying 28 0.44 0.46 0.72 0.28 2.0
##
## PA1 PA2
## SS loadings 10.52 8.14
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.95
## Minimum correlation of possible factor scores 0.92 0.89
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.88 0.772 0.23 1
## pleasing 24 0.88 0.770 0.23 1
## enjoyable 13 0.87 0.755 0.25 1
## likable 19 0.86 0.736 0.26 1
## attractive 3 0.86 0.733 0.27 1
## nice 22 0.85 0.718 0.28 1
## satisfying 28 0.85 0.717 0.28 1
## elegant 11 0.84 0.707 0.29 1
## beautiful 5 0.82 0.678 0.32 1
## delightful 10 0.82 0.670 0.33 1
## lovely 20 0.81 0.661 0.34 1
## tasteful 30 0.80 0.642 0.36 1
## pretty 25 0.80 0.642 0.36 1
## harmonious 16 0.80 0.638 0.36 1
## inviting 18 0.78 0.613 0.39 1
## balanced 4 0.77 0.599 0.40 1
## motivating 21 0.77 0.595 0.40 1
## exciting 14 0.77 0.586 0.41 1
## engaging 12 0.76 0.578 0.42 1
## wellDesigned 31 0.74 0.546 0.45 1
## creative 9 0.68 0.464 0.54 1
## clean 6 0.68 0.458 0.54 1
## artistic 2 0.66 0.439 0.56 1
## fascinating 15 0.66 0.436 0.56 1
## organized 23 0.66 0.433 0.57 1
## interesting 17 0.64 0.412 0.59 1
## sophisticated 29 0.63 0.395 0.61 1
## colorHarmonious 8 0.62 0.379 0.62 1
## professional 26 0.61 0.375 0.62 1
## cluttered 7 0.45 0.199 0.80 1
## provoking 27 0.27 0.075 0.92 1
##
## PA1
## SS loadings 17.42
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 434 and the objective function was 5.16
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.78 0.13 0.62 0.38 1.1
## clean 6 0.75 0.19 0.60 0.40 1.1
## wellDesigned 31 0.74 0.29 0.63 0.37 1.3
## balanced 4 0.72 0.36 0.65 0.35 1.5
## inviting 18 0.68 0.41 0.64 0.36 1.6
## elegant 11 0.68 0.51 0.71 0.29 1.9
## harmonious 16 0.67 0.45 0.65 0.35 1.8
## nice 22 0.66 0.54 0.72 0.28 1.9
## lovely 20 0.65 0.50 0.66 0.34 1.9
## pleasing 24 0.63 0.61 0.77 0.23 2.0
## tasteful 30 0.62 0.51 0.64 0.36 1.9
## professional 26 0.62 0.24 0.43 0.57 1.3
## delightful 10 0.61 0.54 0.67 0.33 2.0
## motivating 21 0.60 0.49 0.60 0.40 1.9
## engaging 12 0.55 0.52 0.58 0.42 2.0
## sophisticated 29 0.54 0.34 0.41 0.59 1.7
## colorHarmonious 8 0.50 0.36 0.38 0.62 1.8
## cluttered 7 0.47 0.15 0.24 0.76 1.2
## artistic 2 0.24 0.72 0.59 0.41 1.2
## exciting 14 0.40 0.70 0.65 0.35 1.6
## pretty 25 0.47 0.68 0.68 0.32 1.8
## appealing 1 0.57 0.68 0.79 0.21 1.9
## attractive 3 0.55 0.67 0.75 0.25 1.9
## creative 9 0.32 0.67 0.54 0.46 1.4
## enjoyable 13 0.57 0.66 0.76 0.24 2.0
## beautiful 5 0.54 0.63 0.69 0.31 1.9
## fascinating 15 0.32 0.63 0.50 0.50 1.5
## interesting 17 0.31 0.62 0.48 0.52 1.5
## likable 19 0.60 0.61 0.74 0.26 2.0
## satisfying 28 0.60 0.60 0.72 0.28 2.0
## provoking 27 0.00 0.41 0.17 0.83 1.0
##
## PA1 PA2
## SS loadings 10.13 8.53
## Proportion Var 0.33 0.28
## Cumulative Var 0.33 0.60
## Proportion Explained 0.54 0.46
## Cumulative Proportion 0.54 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.93 0.92
## Multiple R square of scores with factors 0.87 0.85
## Minimum correlation of possible factor scores 0.75 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.99 -0.31 0.62 0.38 1.2
## clean 6 0.92 -0.21 0.60 0.40 1.1
## wellDesigned 31 0.85 -0.07 0.63 0.37 1.0
## balanced 4 0.77 0.04 0.65 0.35 1.0
## professional 26 0.70 -0.06 0.43 0.57 1.0
## inviting 18 0.68 0.14 0.64 0.36 1.1
## harmonious 16 0.64 0.20 0.65 0.35 1.2
## elegant 11 0.62 0.28 0.71 0.29 1.4
## lovely 20 0.58 0.28 0.66 0.34 1.4
## nice 22 0.57 0.33 0.72 0.28 1.6
## cluttered 7 0.55 -0.09 0.24 0.76 1.1
## tasteful 30 0.54 0.31 0.64 0.36 1.6
## sophisticated 29 0.54 0.13 0.41 0.59 1.1
## motivating 21 0.52 0.30 0.60 0.40 1.6
## delightful 10 0.51 0.36 0.67 0.33 1.8
## pleasing 24 0.49 0.44 0.77 0.23 2.0
## colorHarmonious 8 0.46 0.19 0.38 0.62 1.3
## engaging 12 0.43 0.38 0.58 0.42 2.0
## artistic 2 -0.12 0.85 0.59 0.41 1.0
## creative 9 0.02 0.72 0.54 0.46 1.0
## exciting 14 0.11 0.72 0.65 0.35 1.0
## fascinating 15 0.05 0.67 0.50 0.50 1.0
## interesting 17 0.03 0.67 0.48 0.52 1.0
## pretty 25 0.22 0.65 0.68 0.32 1.2
## appealing 1 0.36 0.58 0.79 0.21 1.7
## provoking 27 -0.27 0.58 0.17 0.83 1.4
## attractive 3 0.34 0.58 0.75 0.25 1.6
## enjoyable 13 0.38 0.55 0.76 0.24 1.8
## beautiful 5 0.34 0.54 0.69 0.31 1.7
## likable 19 0.45 0.47 0.74 0.26 2.0
## satisfying 28 0.44 0.46 0.72 0.28 2.0
##
## PA1 PA2
## SS loadings 10.52 8.14
## Proportion Var 0.34 0.26
## Cumulative Var 0.34 0.60
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.76
## PA2 0.76 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 29.01
## The degrees of freedom for the model are 404 and the objective function was 3.94
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.96 0.95
## Minimum correlation of possible factor scores 0.92 0.89
##
##
## ## Image 11
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.756 0.24 1
## delightful 10 0.86 0.738 0.26 1
## lovely 20 0.86 0.732 0.27 1
## satisfying 28 0.86 0.731 0.27 1
## enjoyable 13 0.85 0.728 0.27 1
## appealing 1 0.85 0.725 0.27 1
## likable 19 0.85 0.721 0.28 1
## beautiful 5 0.85 0.718 0.28 1
## attractive 3 0.85 0.715 0.29 1
## nice 22 0.84 0.708 0.29 1
## pretty 25 0.84 0.698 0.30 1
## inviting 18 0.83 0.696 0.30 1
## exciting 14 0.82 0.674 0.33 1
## tasteful 30 0.82 0.669 0.33 1
## engaging 12 0.79 0.630 0.37 1
## motivating 21 0.78 0.615 0.38 1
## harmonious 16 0.77 0.596 0.40 1
## wellDesigned 31 0.76 0.571 0.43 1
## elegant 11 0.76 0.571 0.43 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.73 0.531 0.47 1
## clean 6 0.71 0.504 0.50 1
## interesting 17 0.70 0.490 0.51 1
## creative 9 0.65 0.424 0.58 1
## artistic 2 0.64 0.416 0.58 1
## organized 23 0.64 0.409 0.59 1
## sophisticated 29 0.63 0.398 0.60 1
## professional 26 0.52 0.273 0.73 1
## colorHarmonious 8 0.51 0.257 0.74 1
## provoking 27 0.40 0.162 0.84 1
## cluttered 7 0.21 0.043 0.96 1
##
## PA1
## SS loadings 17.44
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 434 and the objective function was 6.32
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.37 0.756 0.24 1.4
## interesting 17 0.76 0.23 0.625 0.37 1.2
## creative 9 0.74 0.18 0.577 0.42 1.1
## fascinating 15 0.73 0.29 0.621 0.38 1.3
## engaging 12 0.73 0.39 0.679 0.32 1.5
## artistic 2 0.70 0.21 0.533 0.47 1.2
## pretty 25 0.70 0.48 0.716 0.28 1.8
## attractive 3 0.69 0.50 0.728 0.27 1.8
## enjoyable 13 0.68 0.53 0.734 0.27 1.9
## beautiful 5 0.64 0.55 0.718 0.28 2.0
## nice 22 0.63 0.55 0.708 0.29 2.0
## delightful 10 0.63 0.58 0.736 0.26 2.0
## lovely 20 0.62 0.58 0.730 0.27 2.0
## appealing 1 0.62 0.58 0.723 0.28 2.0
## likable 19 0.61 0.59 0.719 0.28 2.0
## provoking 27 0.55 0.01 0.304 0.70 1.0
## colorHarmonious 8 0.41 0.31 0.260 0.74 1.9
## clean 6 0.21 0.82 0.715 0.29 1.1
## organized 23 0.17 0.75 0.599 0.40 1.1
## elegant 11 0.36 0.72 0.653 0.35 1.5
## balanced 4 0.33 0.72 0.634 0.37 1.4
## wellDesigned 31 0.37 0.71 0.642 0.36 1.5
## satisfying 28 0.56 0.65 0.737 0.26 2.0
## professional 26 0.11 0.65 0.430 0.57 1.1
## inviting 18 0.55 0.63 0.700 0.30 2.0
## pleasing 24 0.61 0.62 0.754 0.25 2.0
## harmonious 16 0.48 0.61 0.608 0.39 1.9
## tasteful 30 0.56 0.60 0.670 0.33 2.0
## sophisticated 29 0.31 0.59 0.447 0.55 1.5
## motivating 21 0.55 0.56 0.614 0.39 2.0
## cluttered 7 0.05 0.25 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 9.94 9.20
## Proportion Var 0.32 0.30
## Cumulative Var 0.32 0.62
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.95
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.81 0.79
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.89 -0.19 0.577 0.42 1.1
## interesting 17 0.89 -0.14 0.625 0.37 1.0
## exciting 14 0.84 0.04 0.756 0.24 1.0
## artistic 2 0.82 -0.13 0.533 0.47 1.1
## fascinating 15 0.81 -0.03 0.621 0.38 1.0
## engaging 12 0.75 0.10 0.679 0.32 1.0
## provoking 27 0.73 -0.31 0.304 0.70 1.3
## pretty 25 0.66 0.23 0.716 0.28 1.2
## attractive 3 0.64 0.26 0.728 0.27 1.3
## enjoyable 13 0.60 0.31 0.734 0.27 1.5
## beautiful 5 0.54 0.37 0.718 0.28 1.8
## nice 22 0.53 0.37 0.708 0.29 1.8
## delightful 10 0.51 0.41 0.736 0.26 1.9
## appealing 1 0.50 0.41 0.723 0.28 1.9
## lovely 20 0.50 0.42 0.730 0.27 1.9
## likable 19 0.48 0.43 0.719 0.28 2.0
## colorHarmonious 8 0.37 0.18 0.260 0.74 1.4
## clean 6 -0.19 0.97 0.715 0.29 1.1
## organized 23 -0.20 0.91 0.599 0.40 1.1
## professional 26 -0.22 0.80 0.430 0.57 1.2
## balanced 4 0.03 0.78 0.634 0.37 1.0
## elegant 11 0.06 0.76 0.653 0.35 1.0
## wellDesigned 31 0.09 0.74 0.642 0.36 1.0
## sophisticated 29 0.07 0.62 0.447 0.55 1.0
## satisfying 28 0.38 0.54 0.737 0.26 1.8
## harmonious 16 0.29 0.54 0.608 0.39 1.5
## inviting 18 0.38 0.52 0.700 0.30 1.8
## tasteful 30 0.40 0.48 0.670 0.33 1.9
## pleasing 24 0.46 0.47 0.754 0.25 2.0
## motivating 21 0.41 0.43 0.614 0.39 2.0
## cluttered 7 -0.07 0.30 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 10.15 8.98
## Proportion Var 0.33 0.29
## Cumulative Var 0.33 0.62
## Proportion Explained 0.53 0.47
## Cumulative Proportion 0.53 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.756 0.24 1
## delightful 10 0.86 0.738 0.26 1
## lovely 20 0.86 0.732 0.27 1
## satisfying 28 0.86 0.731 0.27 1
## enjoyable 13 0.85 0.728 0.27 1
## appealing 1 0.85 0.725 0.27 1
## likable 19 0.85 0.721 0.28 1
## beautiful 5 0.85 0.718 0.28 1
## attractive 3 0.85 0.715 0.29 1
## nice 22 0.84 0.708 0.29 1
## pretty 25 0.84 0.698 0.30 1
## inviting 18 0.83 0.696 0.30 1
## exciting 14 0.82 0.674 0.33 1
## tasteful 30 0.82 0.669 0.33 1
## engaging 12 0.79 0.630 0.37 1
## motivating 21 0.78 0.615 0.38 1
## harmonious 16 0.77 0.596 0.40 1
## wellDesigned 31 0.76 0.571 0.43 1
## elegant 11 0.76 0.571 0.43 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.73 0.531 0.47 1
## clean 6 0.71 0.504 0.50 1
## interesting 17 0.70 0.490 0.51 1
## creative 9 0.65 0.424 0.58 1
## artistic 2 0.64 0.416 0.58 1
## organized 23 0.64 0.409 0.59 1
## sophisticated 29 0.63 0.398 0.60 1
## professional 26 0.52 0.273 0.73 1
## colorHarmonious 8 0.51 0.257 0.74 1
## provoking 27 0.40 0.162 0.84 1
## cluttered 7 0.21 0.043 0.96 1
##
## PA1
## SS loadings 17.44
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 434 and the objective function was 6.32
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.37 0.756 0.24 1.4
## interesting 17 0.76 0.23 0.625 0.37 1.2
## creative 9 0.74 0.18 0.577 0.42 1.1
## fascinating 15 0.73 0.29 0.621 0.38 1.3
## engaging 12 0.73 0.39 0.679 0.32 1.5
## artistic 2 0.70 0.21 0.533 0.47 1.2
## pretty 25 0.70 0.48 0.716 0.28 1.8
## attractive 3 0.69 0.50 0.728 0.27 1.8
## enjoyable 13 0.68 0.53 0.734 0.27 1.9
## beautiful 5 0.64 0.55 0.718 0.28 2.0
## nice 22 0.63 0.55 0.708 0.29 2.0
## delightful 10 0.63 0.58 0.736 0.26 2.0
## lovely 20 0.62 0.58 0.730 0.27 2.0
## appealing 1 0.62 0.58 0.723 0.28 2.0
## likable 19 0.61 0.59 0.719 0.28 2.0
## provoking 27 0.55 0.01 0.304 0.70 1.0
## colorHarmonious 8 0.41 0.31 0.260 0.74 1.9
## clean 6 0.21 0.82 0.715 0.29 1.1
## organized 23 0.17 0.75 0.599 0.40 1.1
## elegant 11 0.36 0.72 0.653 0.35 1.5
## balanced 4 0.33 0.72 0.634 0.37 1.4
## wellDesigned 31 0.37 0.71 0.642 0.36 1.5
## satisfying 28 0.56 0.65 0.737 0.26 2.0
## professional 26 0.11 0.65 0.430 0.57 1.1
## inviting 18 0.55 0.63 0.700 0.30 2.0
## pleasing 24 0.61 0.62 0.754 0.25 2.0
## harmonious 16 0.48 0.61 0.608 0.39 1.9
## tasteful 30 0.56 0.60 0.670 0.33 2.0
## sophisticated 29 0.31 0.59 0.447 0.55 1.5
## motivating 21 0.55 0.56 0.614 0.39 2.0
## cluttered 7 0.05 0.25 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 9.94 9.20
## Proportion Var 0.32 0.30
## Cumulative Var 0.32 0.62
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.95
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.81 0.79
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.89 -0.19 0.577 0.42 1.1
## interesting 17 0.89 -0.14 0.625 0.37 1.0
## exciting 14 0.84 0.04 0.756 0.24 1.0
## artistic 2 0.82 -0.13 0.533 0.47 1.1
## fascinating 15 0.81 -0.03 0.621 0.38 1.0
## engaging 12 0.75 0.10 0.679 0.32 1.0
## provoking 27 0.73 -0.31 0.304 0.70 1.3
## pretty 25 0.66 0.23 0.716 0.28 1.2
## attractive 3 0.64 0.26 0.728 0.27 1.3
## enjoyable 13 0.60 0.31 0.734 0.27 1.5
## beautiful 5 0.54 0.37 0.718 0.28 1.8
## nice 22 0.53 0.37 0.708 0.29 1.8
## delightful 10 0.51 0.41 0.736 0.26 1.9
## appealing 1 0.50 0.41 0.723 0.28 1.9
## lovely 20 0.50 0.42 0.730 0.27 1.9
## likable 19 0.48 0.43 0.719 0.28 2.0
## colorHarmonious 8 0.37 0.18 0.260 0.74 1.4
## clean 6 -0.19 0.97 0.715 0.29 1.1
## organized 23 -0.20 0.91 0.599 0.40 1.1
## professional 26 -0.22 0.80 0.430 0.57 1.2
## balanced 4 0.03 0.78 0.634 0.37 1.0
## elegant 11 0.06 0.76 0.653 0.35 1.0
## wellDesigned 31 0.09 0.74 0.642 0.36 1.0
## sophisticated 29 0.07 0.62 0.447 0.55 1.0
## satisfying 28 0.38 0.54 0.737 0.26 1.8
## harmonious 16 0.29 0.54 0.608 0.39 1.5
## inviting 18 0.38 0.52 0.700 0.30 1.8
## tasteful 30 0.40 0.48 0.670 0.33 1.9
## pleasing 24 0.46 0.47 0.754 0.25 2.0
## motivating 21 0.41 0.43 0.614 0.39 2.0
## cluttered 7 -0.07 0.30 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 10.15 8.98
## Proportion Var 0.33 0.29
## Cumulative Var 0.33 0.62
## Proportion Explained 0.53 0.47
## Cumulative Proportion 0.53 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.756 0.24 1
## delightful 10 0.86 0.738 0.26 1
## lovely 20 0.86 0.732 0.27 1
## satisfying 28 0.86 0.731 0.27 1
## enjoyable 13 0.85 0.728 0.27 1
## appealing 1 0.85 0.725 0.27 1
## likable 19 0.85 0.721 0.28 1
## beautiful 5 0.85 0.718 0.28 1
## attractive 3 0.85 0.715 0.29 1
## nice 22 0.84 0.708 0.29 1
## pretty 25 0.84 0.698 0.30 1
## inviting 18 0.83 0.696 0.30 1
## exciting 14 0.82 0.674 0.33 1
## tasteful 30 0.82 0.669 0.33 1
## engaging 12 0.79 0.630 0.37 1
## motivating 21 0.78 0.615 0.38 1
## harmonious 16 0.77 0.596 0.40 1
## wellDesigned 31 0.76 0.571 0.43 1
## elegant 11 0.76 0.571 0.43 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.73 0.531 0.47 1
## clean 6 0.71 0.504 0.50 1
## interesting 17 0.70 0.490 0.51 1
## creative 9 0.65 0.424 0.58 1
## artistic 2 0.64 0.416 0.58 1
## organized 23 0.64 0.409 0.59 1
## sophisticated 29 0.63 0.398 0.60 1
## professional 26 0.52 0.273 0.73 1
## colorHarmonious 8 0.51 0.257 0.74 1
## provoking 27 0.40 0.162 0.84 1
## cluttered 7 0.21 0.043 0.96 1
##
## PA1
## SS loadings 17.44
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 434 and the objective function was 6.32
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.37 0.756 0.24 1.4
## interesting 17 0.76 0.23 0.625 0.37 1.2
## creative 9 0.74 0.18 0.577 0.42 1.1
## fascinating 15 0.73 0.29 0.621 0.38 1.3
## engaging 12 0.73 0.39 0.679 0.32 1.5
## artistic 2 0.70 0.21 0.533 0.47 1.2
## pretty 25 0.70 0.48 0.716 0.28 1.8
## attractive 3 0.69 0.50 0.728 0.27 1.8
## enjoyable 13 0.68 0.53 0.734 0.27 1.9
## beautiful 5 0.64 0.55 0.718 0.28 2.0
## nice 22 0.63 0.55 0.708 0.29 2.0
## delightful 10 0.63 0.58 0.736 0.26 2.0
## lovely 20 0.62 0.58 0.730 0.27 2.0
## appealing 1 0.62 0.58 0.723 0.28 2.0
## likable 19 0.61 0.59 0.719 0.28 2.0
## provoking 27 0.55 0.01 0.304 0.70 1.0
## colorHarmonious 8 0.41 0.31 0.260 0.74 1.9
## clean 6 0.21 0.82 0.715 0.29 1.1
## organized 23 0.17 0.75 0.599 0.40 1.1
## elegant 11 0.36 0.72 0.653 0.35 1.5
## balanced 4 0.33 0.72 0.634 0.37 1.4
## wellDesigned 31 0.37 0.71 0.642 0.36 1.5
## satisfying 28 0.56 0.65 0.737 0.26 2.0
## professional 26 0.11 0.65 0.430 0.57 1.1
## inviting 18 0.55 0.63 0.700 0.30 2.0
## pleasing 24 0.61 0.62 0.754 0.25 2.0
## harmonious 16 0.48 0.61 0.608 0.39 1.9
## tasteful 30 0.56 0.60 0.670 0.33 2.0
## sophisticated 29 0.31 0.59 0.447 0.55 1.5
## motivating 21 0.55 0.56 0.614 0.39 2.0
## cluttered 7 0.05 0.25 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 9.94 9.20
## Proportion Var 0.32 0.30
## Cumulative Var 0.32 0.62
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.95
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.81 0.79
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.89 -0.19 0.577 0.42 1.1
## interesting 17 0.89 -0.14 0.625 0.37 1.0
## exciting 14 0.84 0.04 0.756 0.24 1.0
## artistic 2 0.82 -0.13 0.533 0.47 1.1
## fascinating 15 0.81 -0.03 0.621 0.38 1.0
## engaging 12 0.75 0.10 0.679 0.32 1.0
## provoking 27 0.73 -0.31 0.304 0.70 1.3
## pretty 25 0.66 0.23 0.716 0.28 1.2
## attractive 3 0.64 0.26 0.728 0.27 1.3
## enjoyable 13 0.60 0.31 0.734 0.27 1.5
## beautiful 5 0.54 0.37 0.718 0.28 1.8
## nice 22 0.53 0.37 0.708 0.29 1.8
## delightful 10 0.51 0.41 0.736 0.26 1.9
## appealing 1 0.50 0.41 0.723 0.28 1.9
## lovely 20 0.50 0.42 0.730 0.27 1.9
## likable 19 0.48 0.43 0.719 0.28 2.0
## colorHarmonious 8 0.37 0.18 0.260 0.74 1.4
## clean 6 -0.19 0.97 0.715 0.29 1.1
## organized 23 -0.20 0.91 0.599 0.40 1.1
## professional 26 -0.22 0.80 0.430 0.57 1.2
## balanced 4 0.03 0.78 0.634 0.37 1.0
## elegant 11 0.06 0.76 0.653 0.35 1.0
## wellDesigned 31 0.09 0.74 0.642 0.36 1.0
## sophisticated 29 0.07 0.62 0.447 0.55 1.0
## satisfying 28 0.38 0.54 0.737 0.26 1.8
## harmonious 16 0.29 0.54 0.608 0.39 1.5
## inviting 18 0.38 0.52 0.700 0.30 1.8
## tasteful 30 0.40 0.48 0.670 0.33 1.9
## pleasing 24 0.46 0.47 0.754 0.25 2.0
## motivating 21 0.41 0.43 0.614 0.39 2.0
## cluttered 7 -0.07 0.30 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 10.15 8.98
## Proportion Var 0.33 0.29
## Cumulative Var 0.33 0.62
## Proportion Explained 0.53 0.47
## Cumulative Proportion 0.53 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.756 0.24 1
## delightful 10 0.86 0.738 0.26 1
## lovely 20 0.86 0.732 0.27 1
## satisfying 28 0.86 0.731 0.27 1
## enjoyable 13 0.85 0.728 0.27 1
## appealing 1 0.85 0.725 0.27 1
## likable 19 0.85 0.721 0.28 1
## beautiful 5 0.85 0.718 0.28 1
## attractive 3 0.85 0.715 0.29 1
## nice 22 0.84 0.708 0.29 1
## pretty 25 0.84 0.698 0.30 1
## inviting 18 0.83 0.696 0.30 1
## exciting 14 0.82 0.674 0.33 1
## tasteful 30 0.82 0.669 0.33 1
## engaging 12 0.79 0.630 0.37 1
## motivating 21 0.78 0.615 0.38 1
## harmonious 16 0.77 0.596 0.40 1
## wellDesigned 31 0.76 0.571 0.43 1
## elegant 11 0.76 0.571 0.43 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.73 0.531 0.47 1
## clean 6 0.71 0.504 0.50 1
## interesting 17 0.70 0.490 0.51 1
## creative 9 0.65 0.424 0.58 1
## artistic 2 0.64 0.416 0.58 1
## organized 23 0.64 0.409 0.59 1
## sophisticated 29 0.63 0.398 0.60 1
## professional 26 0.52 0.273 0.73 1
## colorHarmonious 8 0.51 0.257 0.74 1
## provoking 27 0.40 0.162 0.84 1
## cluttered 7 0.21 0.043 0.96 1
##
## PA1
## SS loadings 17.44
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 434 and the objective function was 6.32
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.37 0.756 0.24 1.4
## interesting 17 0.76 0.23 0.625 0.37 1.2
## creative 9 0.74 0.18 0.577 0.42 1.1
## fascinating 15 0.73 0.29 0.621 0.38 1.3
## engaging 12 0.73 0.39 0.679 0.32 1.5
## artistic 2 0.70 0.21 0.533 0.47 1.2
## pretty 25 0.70 0.48 0.716 0.28 1.8
## attractive 3 0.69 0.50 0.728 0.27 1.8
## enjoyable 13 0.68 0.53 0.734 0.27 1.9
## beautiful 5 0.64 0.55 0.718 0.28 2.0
## nice 22 0.63 0.55 0.708 0.29 2.0
## delightful 10 0.63 0.58 0.736 0.26 2.0
## lovely 20 0.62 0.58 0.730 0.27 2.0
## appealing 1 0.62 0.58 0.723 0.28 2.0
## likable 19 0.61 0.59 0.719 0.28 2.0
## provoking 27 0.55 0.01 0.304 0.70 1.0
## colorHarmonious 8 0.41 0.31 0.260 0.74 1.9
## clean 6 0.21 0.82 0.715 0.29 1.1
## organized 23 0.17 0.75 0.599 0.40 1.1
## elegant 11 0.36 0.72 0.653 0.35 1.5
## balanced 4 0.33 0.72 0.634 0.37 1.4
## wellDesigned 31 0.37 0.71 0.642 0.36 1.5
## satisfying 28 0.56 0.65 0.737 0.26 2.0
## professional 26 0.11 0.65 0.430 0.57 1.1
## inviting 18 0.55 0.63 0.700 0.30 2.0
## pleasing 24 0.61 0.62 0.754 0.25 2.0
## harmonious 16 0.48 0.61 0.608 0.39 1.9
## tasteful 30 0.56 0.60 0.670 0.33 2.0
## sophisticated 29 0.31 0.59 0.447 0.55 1.5
## motivating 21 0.55 0.56 0.614 0.39 2.0
## cluttered 7 0.05 0.25 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 9.94 9.20
## Proportion Var 0.32 0.30
## Cumulative Var 0.32 0.62
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.95
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.81 0.79
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.89 -0.19 0.577 0.42 1.1
## interesting 17 0.89 -0.14 0.625 0.37 1.0
## exciting 14 0.84 0.04 0.756 0.24 1.0
## artistic 2 0.82 -0.13 0.533 0.47 1.1
## fascinating 15 0.81 -0.03 0.621 0.38 1.0
## engaging 12 0.75 0.10 0.679 0.32 1.0
## provoking 27 0.73 -0.31 0.304 0.70 1.3
## pretty 25 0.66 0.23 0.716 0.28 1.2
## attractive 3 0.64 0.26 0.728 0.27 1.3
## enjoyable 13 0.60 0.31 0.734 0.27 1.5
## beautiful 5 0.54 0.37 0.718 0.28 1.8
## nice 22 0.53 0.37 0.708 0.29 1.8
## delightful 10 0.51 0.41 0.736 0.26 1.9
## appealing 1 0.50 0.41 0.723 0.28 1.9
## lovely 20 0.50 0.42 0.730 0.27 1.9
## likable 19 0.48 0.43 0.719 0.28 2.0
## colorHarmonious 8 0.37 0.18 0.260 0.74 1.4
## clean 6 -0.19 0.97 0.715 0.29 1.1
## organized 23 -0.20 0.91 0.599 0.40 1.1
## professional 26 -0.22 0.80 0.430 0.57 1.2
## balanced 4 0.03 0.78 0.634 0.37 1.0
## elegant 11 0.06 0.76 0.653 0.35 1.0
## wellDesigned 31 0.09 0.74 0.642 0.36 1.0
## sophisticated 29 0.07 0.62 0.447 0.55 1.0
## satisfying 28 0.38 0.54 0.737 0.26 1.8
## harmonious 16 0.29 0.54 0.608 0.39 1.5
## inviting 18 0.38 0.52 0.700 0.30 1.8
## tasteful 30 0.40 0.48 0.670 0.33 1.9
## pleasing 24 0.46 0.47 0.754 0.25 2.0
## motivating 21 0.41 0.43 0.614 0.39 2.0
## cluttered 7 -0.07 0.30 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 10.15 8.98
## Proportion Var 0.33 0.29
## Cumulative Var 0.33 0.62
## Proportion Explained 0.53 0.47
## Cumulative Proportion 0.53 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## pleasing 24 0.87 0.756 0.24 1
## delightful 10 0.86 0.738 0.26 1
## lovely 20 0.86 0.732 0.27 1
## satisfying 28 0.86 0.731 0.27 1
## enjoyable 13 0.85 0.728 0.27 1
## appealing 1 0.85 0.725 0.27 1
## likable 19 0.85 0.721 0.28 1
## beautiful 5 0.85 0.718 0.28 1
## attractive 3 0.85 0.715 0.29 1
## nice 22 0.84 0.708 0.29 1
## pretty 25 0.84 0.698 0.30 1
## inviting 18 0.83 0.696 0.30 1
## exciting 14 0.82 0.674 0.33 1
## tasteful 30 0.82 0.669 0.33 1
## engaging 12 0.79 0.630 0.37 1
## motivating 21 0.78 0.615 0.38 1
## harmonious 16 0.77 0.596 0.40 1
## wellDesigned 31 0.76 0.571 0.43 1
## elegant 11 0.76 0.571 0.43 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.73 0.531 0.47 1
## clean 6 0.71 0.504 0.50 1
## interesting 17 0.70 0.490 0.51 1
## creative 9 0.65 0.424 0.58 1
## artistic 2 0.64 0.416 0.58 1
## organized 23 0.64 0.409 0.59 1
## sophisticated 29 0.63 0.398 0.60 1
## professional 26 0.52 0.273 0.73 1
## colorHarmonious 8 0.51 0.257 0.74 1
## provoking 27 0.40 0.162 0.84 1
## cluttered 7 0.21 0.043 0.96 1
##
## PA1
## SS loadings 17.44
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 434 and the objective function was 6.32
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## exciting 14 0.79 0.37 0.756 0.24 1.4
## interesting 17 0.76 0.23 0.625 0.37 1.2
## creative 9 0.74 0.18 0.577 0.42 1.1
## fascinating 15 0.73 0.29 0.621 0.38 1.3
## engaging 12 0.73 0.39 0.679 0.32 1.5
## artistic 2 0.70 0.21 0.533 0.47 1.2
## pretty 25 0.70 0.48 0.716 0.28 1.8
## attractive 3 0.69 0.50 0.728 0.27 1.8
## enjoyable 13 0.68 0.53 0.734 0.27 1.9
## beautiful 5 0.64 0.55 0.718 0.28 2.0
## nice 22 0.63 0.55 0.708 0.29 2.0
## delightful 10 0.63 0.58 0.736 0.26 2.0
## lovely 20 0.62 0.58 0.730 0.27 2.0
## appealing 1 0.62 0.58 0.723 0.28 2.0
## likable 19 0.61 0.59 0.719 0.28 2.0
## provoking 27 0.55 0.01 0.304 0.70 1.0
## colorHarmonious 8 0.41 0.31 0.260 0.74 1.9
## clean 6 0.21 0.82 0.715 0.29 1.1
## organized 23 0.17 0.75 0.599 0.40 1.1
## elegant 11 0.36 0.72 0.653 0.35 1.5
## balanced 4 0.33 0.72 0.634 0.37 1.4
## wellDesigned 31 0.37 0.71 0.642 0.36 1.5
## satisfying 28 0.56 0.65 0.737 0.26 2.0
## professional 26 0.11 0.65 0.430 0.57 1.1
## inviting 18 0.55 0.63 0.700 0.30 2.0
## pleasing 24 0.61 0.62 0.754 0.25 2.0
## harmonious 16 0.48 0.61 0.608 0.39 1.9
## tasteful 30 0.56 0.60 0.670 0.33 2.0
## sophisticated 29 0.31 0.59 0.447 0.55 1.5
## motivating 21 0.55 0.56 0.614 0.39 2.0
## cluttered 7 0.05 0.25 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 9.94 9.20
## Proportion Var 0.32 0.30
## Cumulative Var 0.32 0.62
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.95
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.81 0.79
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## creative 9 0.89 -0.19 0.577 0.42 1.1
## interesting 17 0.89 -0.14 0.625 0.37 1.0
## exciting 14 0.84 0.04 0.756 0.24 1.0
## artistic 2 0.82 -0.13 0.533 0.47 1.1
## fascinating 15 0.81 -0.03 0.621 0.38 1.0
## engaging 12 0.75 0.10 0.679 0.32 1.0
## provoking 27 0.73 -0.31 0.304 0.70 1.3
## pretty 25 0.66 0.23 0.716 0.28 1.2
## attractive 3 0.64 0.26 0.728 0.27 1.3
## enjoyable 13 0.60 0.31 0.734 0.27 1.5
## beautiful 5 0.54 0.37 0.718 0.28 1.8
## nice 22 0.53 0.37 0.708 0.29 1.8
## delightful 10 0.51 0.41 0.736 0.26 1.9
## appealing 1 0.50 0.41 0.723 0.28 1.9
## lovely 20 0.50 0.42 0.730 0.27 1.9
## likable 19 0.48 0.43 0.719 0.28 2.0
## colorHarmonious 8 0.37 0.18 0.260 0.74 1.4
## clean 6 -0.19 0.97 0.715 0.29 1.1
## organized 23 -0.20 0.91 0.599 0.40 1.1
## professional 26 -0.22 0.80 0.430 0.57 1.2
## balanced 4 0.03 0.78 0.634 0.37 1.0
## elegant 11 0.06 0.76 0.653 0.35 1.0
## wellDesigned 31 0.09 0.74 0.642 0.36 1.0
## sophisticated 29 0.07 0.62 0.447 0.55 1.0
## satisfying 28 0.38 0.54 0.737 0.26 1.8
## harmonious 16 0.29 0.54 0.608 0.39 1.5
## inviting 18 0.38 0.52 0.700 0.30 1.8
## tasteful 30 0.40 0.48 0.670 0.33 1.9
## pleasing 24 0.46 0.47 0.754 0.25 2.0
## motivating 21 0.41 0.43 0.614 0.39 2.0
## cluttered 7 -0.07 0.30 0.064 0.94 1.1
##
## PA1 PA2
## SS loadings 10.15 8.98
## Proportion Var 0.33 0.29
## Cumulative Var 0.33 0.62
## Proportion Explained 0.53 0.47
## Cumulative Proportion 0.53 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.73
## PA2 0.73 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.52
## The degrees of freedom for the model are 404 and the objective function was 4.38
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Image 12
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.89 0.7856 0.21 1
## pleasing 24 0.88 0.7768 0.22 1
## enjoyable 13 0.88 0.7728 0.23 1
## delightful 10 0.88 0.7665 0.23 1
## appealing 1 0.88 0.7658 0.23 1
## satisfying 28 0.87 0.7625 0.24 1
## attractive 3 0.87 0.7591 0.24 1
## lovely 20 0.86 0.7360 0.26 1
## beautiful 5 0.85 0.7302 0.27 1
## pretty 25 0.85 0.7196 0.28 1
## nice 22 0.82 0.6727 0.33 1
## wellDesigned 31 0.81 0.6639 0.34 1
## elegant 11 0.80 0.6454 0.35 1
## harmonious 16 0.80 0.6356 0.36 1
## inviting 18 0.78 0.6007 0.40 1
## fascinating 15 0.77 0.5983 0.40 1
## exciting 14 0.77 0.5939 0.41 1
## engaging 12 0.77 0.5864 0.41 1
## tasteful 30 0.76 0.5750 0.42 1
## sophisticated 29 0.75 0.5642 0.44 1
## interesting 17 0.73 0.5309 0.47 1
## motivating 21 0.71 0.5097 0.49 1
## clean 6 0.71 0.5007 0.50 1
## artistic 2 0.69 0.4813 0.52 1
## professional 26 0.67 0.4544 0.55 1
## balanced 4 0.66 0.4393 0.56 1
## organized 23 0.66 0.4316 0.57 1
## creative 9 0.64 0.4139 0.59 1
## colorHarmonious 8 0.62 0.3830 0.62 1
## provoking 27 0.32 0.1052 0.89 1
## cluttered 7 -0.05 0.0025 1.00 1
##
## PA1
## SS loadings 17.96
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 434 and the objective function was 5.62
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.84 0.04 0.699 0.30 1.0
## pretty 25 0.76 0.39 0.735 0.26 1.5
## delightful 10 0.76 0.44 0.772 0.23 1.6
## creative 9 0.75 0.06 0.571 0.43 1.0
## beautiful 5 0.75 0.42 0.737 0.26 1.6
## fascinating 15 0.74 0.29 0.637 0.36 1.3
## likable 19 0.74 0.49 0.785 0.21 1.7
## pleasing 24 0.74 0.48 0.777 0.22 1.7
## enjoyable 13 0.73 0.49 0.772 0.23 1.7
## lovely 20 0.73 0.46 0.737 0.26 1.7
## exciting 14 0.71 0.33 0.616 0.38 1.4
## nice 22 0.71 0.42 0.676 0.32 1.6
## attractive 3 0.70 0.51 0.758 0.24 1.8
## satisfying 28 0.70 0.52 0.761 0.24 1.9
## appealing 1 0.69 0.53 0.765 0.23 1.9
## interesting 17 0.68 0.30 0.555 0.44 1.4
## engaging 12 0.64 0.42 0.586 0.41 1.7
## inviting 18 0.61 0.48 0.601 0.40 1.9
## elegant 11 0.60 0.54 0.652 0.35 2.0
## motivating 21 0.60 0.39 0.510 0.49 1.7
## tasteful 30 0.59 0.47 0.575 0.42 1.9
## sophisticated 29 0.59 0.47 0.565 0.44 1.9
## harmonious 16 0.58 0.56 0.649 0.35 2.0
## colorHarmonious 8 0.52 0.34 0.383 0.62 1.7
## provoking 27 0.42 -0.02 0.174 0.83 1.0
## organized 23 0.25 0.80 0.701 0.30 1.2
## clean 6 0.36 0.72 0.652 0.35 1.5
## professional 26 0.32 0.72 0.623 0.38 1.4
## balanced 4 0.36 0.64 0.542 0.46 1.6
## wellDesigned 31 0.57 0.61 0.693 0.31 2.0
## cluttered 7 0.09 -0.21 0.054 0.95 1.4
##
## PA1 PA2
## SS loadings 12.35 6.97
## Proportion Var 0.40 0.22
## Cumulative Var 0.40 0.62
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.92
## Multiple R square of scores with factors 0.92 0.85
## Minimum correlation of possible factor scores 0.83 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.01 -0.34 0.699 0.30 1.2
## creative 9 0.90 -0.27 0.571 0.43 1.2
## fascinating 15 0.79 0.02 0.637 0.36 1.0
## pretty 25 0.77 0.13 0.735 0.26 1.1
## delightful 10 0.74 0.19 0.772 0.23 1.1
## beautiful 5 0.74 0.17 0.737 0.26 1.1
## exciting 14 0.74 0.07 0.616 0.38 1.0
## interesting 17 0.71 0.05 0.555 0.44 1.0
## pleasing 24 0.70 0.25 0.777 0.22 1.2
## likable 19 0.70 0.26 0.785 0.21 1.3
## lovely 20 0.70 0.22 0.737 0.26 1.2
## nice 22 0.69 0.19 0.676 0.32 1.1
## enjoyable 13 0.69 0.26 0.772 0.23 1.3
## attractive 3 0.64 0.30 0.758 0.24 1.4
## satisfying 28 0.63 0.32 0.761 0.24 1.5
## appealing 1 0.62 0.33 0.765 0.23 1.5
## engaging 12 0.60 0.22 0.586 0.41 1.3
## motivating 21 0.57 0.19 0.510 0.49 1.2
## inviting 18 0.54 0.30 0.601 0.40 1.6
## tasteful 30 0.53 0.30 0.575 0.42 1.6
## provoking 27 0.52 -0.22 0.174 0.83 1.3
## sophisticated 29 0.52 0.30 0.565 0.44 1.6
## elegant 11 0.51 0.38 0.652 0.35 1.8
## colorHarmonious 8 0.49 0.18 0.383 0.62 1.3
## harmonious 16 0.47 0.42 0.649 0.35 2.0
## organized 23 -0.04 0.87 0.701 0.30 1.0
## professional 26 0.08 0.74 0.623 0.38 1.0
## clean 6 0.13 0.72 0.652 0.35 1.1
## balanced 4 0.16 0.62 0.542 0.46 1.1
## wellDesigned 31 0.43 0.49 0.693 0.31 2.0
## cluttered 7 0.21 -0.30 0.054 0.95 1.8
##
## PA1 PA2
## SS loadings 13.40 5.92
## Proportion Var 0.43 0.19
## Cumulative Var 0.43 0.62
## Proportion Explained 0.69 0.31
## Cumulative Proportion 0.69 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.64
## PA2 0.64 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.96
## Multiple R square of scores with factors 0.97 0.92
## Minimum correlation of possible factor scores 0.94 0.84
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.89 0.7856 0.21 1
## pleasing 24 0.88 0.7768 0.22 1
## enjoyable 13 0.88 0.7728 0.23 1
## delightful 10 0.88 0.7665 0.23 1
## appealing 1 0.88 0.7658 0.23 1
## satisfying 28 0.87 0.7625 0.24 1
## attractive 3 0.87 0.7591 0.24 1
## lovely 20 0.86 0.7360 0.26 1
## beautiful 5 0.85 0.7302 0.27 1
## pretty 25 0.85 0.7196 0.28 1
## nice 22 0.82 0.6727 0.33 1
## wellDesigned 31 0.81 0.6639 0.34 1
## elegant 11 0.80 0.6454 0.35 1
## harmonious 16 0.80 0.6356 0.36 1
## inviting 18 0.78 0.6007 0.40 1
## fascinating 15 0.77 0.5983 0.40 1
## exciting 14 0.77 0.5939 0.41 1
## engaging 12 0.77 0.5864 0.41 1
## tasteful 30 0.76 0.5750 0.42 1
## sophisticated 29 0.75 0.5642 0.44 1
## interesting 17 0.73 0.5309 0.47 1
## motivating 21 0.71 0.5097 0.49 1
## clean 6 0.71 0.5007 0.50 1
## artistic 2 0.69 0.4813 0.52 1
## professional 26 0.67 0.4544 0.55 1
## balanced 4 0.66 0.4393 0.56 1
## organized 23 0.66 0.4316 0.57 1
## creative 9 0.64 0.4139 0.59 1
## colorHarmonious 8 0.62 0.3830 0.62 1
## provoking 27 0.32 0.1052 0.89 1
## cluttered 7 -0.05 0.0025 1.00 1
##
## PA1
## SS loadings 17.96
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 434 and the objective function was 5.62
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.84 0.04 0.699 0.30 1.0
## pretty 25 0.76 0.39 0.735 0.26 1.5
## delightful 10 0.76 0.44 0.772 0.23 1.6
## creative 9 0.75 0.06 0.571 0.43 1.0
## beautiful 5 0.75 0.42 0.737 0.26 1.6
## fascinating 15 0.74 0.29 0.637 0.36 1.3
## likable 19 0.74 0.49 0.785 0.21 1.7
## pleasing 24 0.74 0.48 0.777 0.22 1.7
## enjoyable 13 0.73 0.49 0.772 0.23 1.7
## lovely 20 0.73 0.46 0.737 0.26 1.7
## exciting 14 0.71 0.33 0.616 0.38 1.4
## nice 22 0.71 0.42 0.676 0.32 1.6
## attractive 3 0.70 0.51 0.758 0.24 1.8
## satisfying 28 0.70 0.52 0.761 0.24 1.9
## appealing 1 0.69 0.53 0.765 0.23 1.9
## interesting 17 0.68 0.30 0.555 0.44 1.4
## engaging 12 0.64 0.42 0.586 0.41 1.7
## inviting 18 0.61 0.48 0.601 0.40 1.9
## elegant 11 0.60 0.54 0.652 0.35 2.0
## motivating 21 0.60 0.39 0.510 0.49 1.7
## tasteful 30 0.59 0.47 0.575 0.42 1.9
## sophisticated 29 0.59 0.47 0.565 0.44 1.9
## harmonious 16 0.58 0.56 0.649 0.35 2.0
## colorHarmonious 8 0.52 0.34 0.383 0.62 1.7
## provoking 27 0.42 -0.02 0.174 0.83 1.0
## organized 23 0.25 0.80 0.701 0.30 1.2
## clean 6 0.36 0.72 0.652 0.35 1.5
## professional 26 0.32 0.72 0.623 0.38 1.4
## balanced 4 0.36 0.64 0.542 0.46 1.6
## wellDesigned 31 0.57 0.61 0.693 0.31 2.0
## cluttered 7 0.09 -0.21 0.054 0.95 1.4
##
## PA1 PA2
## SS loadings 12.35 6.97
## Proportion Var 0.40 0.22
## Cumulative Var 0.40 0.62
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.92
## Multiple R square of scores with factors 0.92 0.85
## Minimum correlation of possible factor scores 0.83 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.01 -0.34 0.699 0.30 1.2
## creative 9 0.90 -0.27 0.571 0.43 1.2
## fascinating 15 0.79 0.02 0.637 0.36 1.0
## pretty 25 0.77 0.13 0.735 0.26 1.1
## delightful 10 0.74 0.19 0.772 0.23 1.1
## beautiful 5 0.74 0.17 0.737 0.26 1.1
## exciting 14 0.74 0.07 0.616 0.38 1.0
## interesting 17 0.71 0.05 0.555 0.44 1.0
## pleasing 24 0.70 0.25 0.777 0.22 1.2
## likable 19 0.70 0.26 0.785 0.21 1.3
## lovely 20 0.70 0.22 0.737 0.26 1.2
## nice 22 0.69 0.19 0.676 0.32 1.1
## enjoyable 13 0.69 0.26 0.772 0.23 1.3
## attractive 3 0.64 0.30 0.758 0.24 1.4
## satisfying 28 0.63 0.32 0.761 0.24 1.5
## appealing 1 0.62 0.33 0.765 0.23 1.5
## engaging 12 0.60 0.22 0.586 0.41 1.3
## motivating 21 0.57 0.19 0.510 0.49 1.2
## inviting 18 0.54 0.30 0.601 0.40 1.6
## tasteful 30 0.53 0.30 0.575 0.42 1.6
## provoking 27 0.52 -0.22 0.174 0.83 1.3
## sophisticated 29 0.52 0.30 0.565 0.44 1.6
## elegant 11 0.51 0.38 0.652 0.35 1.8
## colorHarmonious 8 0.49 0.18 0.383 0.62 1.3
## harmonious 16 0.47 0.42 0.649 0.35 2.0
## organized 23 -0.04 0.87 0.701 0.30 1.0
## professional 26 0.08 0.74 0.623 0.38 1.0
## clean 6 0.13 0.72 0.652 0.35 1.1
## balanced 4 0.16 0.62 0.542 0.46 1.1
## wellDesigned 31 0.43 0.49 0.693 0.31 2.0
## cluttered 7 0.21 -0.30 0.054 0.95 1.8
##
## PA1 PA2
## SS loadings 13.40 5.92
## Proportion Var 0.43 0.19
## Cumulative Var 0.43 0.62
## Proportion Explained 0.69 0.31
## Cumulative Proportion 0.69 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.64
## PA2 0.64 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.96
## Multiple R square of scores with factors 0.97 0.92
## Minimum correlation of possible factor scores 0.94 0.84
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.89 0.7856 0.21 1
## pleasing 24 0.88 0.7768 0.22 1
## enjoyable 13 0.88 0.7728 0.23 1
## delightful 10 0.88 0.7665 0.23 1
## appealing 1 0.88 0.7658 0.23 1
## satisfying 28 0.87 0.7625 0.24 1
## attractive 3 0.87 0.7591 0.24 1
## lovely 20 0.86 0.7360 0.26 1
## beautiful 5 0.85 0.7302 0.27 1
## pretty 25 0.85 0.7196 0.28 1
## nice 22 0.82 0.6727 0.33 1
## wellDesigned 31 0.81 0.6639 0.34 1
## elegant 11 0.80 0.6454 0.35 1
## harmonious 16 0.80 0.6356 0.36 1
## inviting 18 0.78 0.6007 0.40 1
## fascinating 15 0.77 0.5983 0.40 1
## exciting 14 0.77 0.5939 0.41 1
## engaging 12 0.77 0.5864 0.41 1
## tasteful 30 0.76 0.5750 0.42 1
## sophisticated 29 0.75 0.5642 0.44 1
## interesting 17 0.73 0.5309 0.47 1
## motivating 21 0.71 0.5097 0.49 1
## clean 6 0.71 0.5007 0.50 1
## artistic 2 0.69 0.4813 0.52 1
## professional 26 0.67 0.4544 0.55 1
## balanced 4 0.66 0.4393 0.56 1
## organized 23 0.66 0.4316 0.57 1
## creative 9 0.64 0.4139 0.59 1
## colorHarmonious 8 0.62 0.3830 0.62 1
## provoking 27 0.32 0.1052 0.89 1
## cluttered 7 -0.05 0.0025 1.00 1
##
## PA1
## SS loadings 17.96
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 434 and the objective function was 5.62
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.84 0.04 0.699 0.30 1.0
## pretty 25 0.76 0.39 0.735 0.26 1.5
## delightful 10 0.76 0.44 0.772 0.23 1.6
## creative 9 0.75 0.06 0.571 0.43 1.0
## beautiful 5 0.75 0.42 0.737 0.26 1.6
## fascinating 15 0.74 0.29 0.637 0.36 1.3
## likable 19 0.74 0.49 0.785 0.21 1.7
## pleasing 24 0.74 0.48 0.777 0.22 1.7
## enjoyable 13 0.73 0.49 0.772 0.23 1.7
## lovely 20 0.73 0.46 0.737 0.26 1.7
## exciting 14 0.71 0.33 0.616 0.38 1.4
## nice 22 0.71 0.42 0.676 0.32 1.6
## attractive 3 0.70 0.51 0.758 0.24 1.8
## satisfying 28 0.70 0.52 0.761 0.24 1.9
## appealing 1 0.69 0.53 0.765 0.23 1.9
## interesting 17 0.68 0.30 0.555 0.44 1.4
## engaging 12 0.64 0.42 0.586 0.41 1.7
## inviting 18 0.61 0.48 0.601 0.40 1.9
## elegant 11 0.60 0.54 0.652 0.35 2.0
## motivating 21 0.60 0.39 0.510 0.49 1.7
## tasteful 30 0.59 0.47 0.575 0.42 1.9
## sophisticated 29 0.59 0.47 0.565 0.44 1.9
## harmonious 16 0.58 0.56 0.649 0.35 2.0
## colorHarmonious 8 0.52 0.34 0.383 0.62 1.7
## provoking 27 0.42 -0.02 0.174 0.83 1.0
## organized 23 0.25 0.80 0.701 0.30 1.2
## clean 6 0.36 0.72 0.652 0.35 1.5
## professional 26 0.32 0.72 0.623 0.38 1.4
## balanced 4 0.36 0.64 0.542 0.46 1.6
## wellDesigned 31 0.57 0.61 0.693 0.31 2.0
## cluttered 7 0.09 -0.21 0.054 0.95 1.4
##
## PA1 PA2
## SS loadings 12.35 6.97
## Proportion Var 0.40 0.22
## Cumulative Var 0.40 0.62
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.92
## Multiple R square of scores with factors 0.92 0.85
## Minimum correlation of possible factor scores 0.83 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.01 -0.34 0.699 0.30 1.2
## creative 9 0.90 -0.27 0.571 0.43 1.2
## fascinating 15 0.79 0.02 0.637 0.36 1.0
## pretty 25 0.77 0.13 0.735 0.26 1.1
## delightful 10 0.74 0.19 0.772 0.23 1.1
## beautiful 5 0.74 0.17 0.737 0.26 1.1
## exciting 14 0.74 0.07 0.616 0.38 1.0
## interesting 17 0.71 0.05 0.555 0.44 1.0
## pleasing 24 0.70 0.25 0.777 0.22 1.2
## likable 19 0.70 0.26 0.785 0.21 1.3
## lovely 20 0.70 0.22 0.737 0.26 1.2
## nice 22 0.69 0.19 0.676 0.32 1.1
## enjoyable 13 0.69 0.26 0.772 0.23 1.3
## attractive 3 0.64 0.30 0.758 0.24 1.4
## satisfying 28 0.63 0.32 0.761 0.24 1.5
## appealing 1 0.62 0.33 0.765 0.23 1.5
## engaging 12 0.60 0.22 0.586 0.41 1.3
## motivating 21 0.57 0.19 0.510 0.49 1.2
## inviting 18 0.54 0.30 0.601 0.40 1.6
## tasteful 30 0.53 0.30 0.575 0.42 1.6
## provoking 27 0.52 -0.22 0.174 0.83 1.3
## sophisticated 29 0.52 0.30 0.565 0.44 1.6
## elegant 11 0.51 0.38 0.652 0.35 1.8
## colorHarmonious 8 0.49 0.18 0.383 0.62 1.3
## harmonious 16 0.47 0.42 0.649 0.35 2.0
## organized 23 -0.04 0.87 0.701 0.30 1.0
## professional 26 0.08 0.74 0.623 0.38 1.0
## clean 6 0.13 0.72 0.652 0.35 1.1
## balanced 4 0.16 0.62 0.542 0.46 1.1
## wellDesigned 31 0.43 0.49 0.693 0.31 2.0
## cluttered 7 0.21 -0.30 0.054 0.95 1.8
##
## PA1 PA2
## SS loadings 13.40 5.92
## Proportion Var 0.43 0.19
## Cumulative Var 0.43 0.62
## Proportion Explained 0.69 0.31
## Cumulative Proportion 0.69 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.64
## PA2 0.64 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.96
## Multiple R square of scores with factors 0.97 0.92
## Minimum correlation of possible factor scores 0.94 0.84
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.89 0.7856 0.21 1
## pleasing 24 0.88 0.7768 0.22 1
## enjoyable 13 0.88 0.7728 0.23 1
## delightful 10 0.88 0.7665 0.23 1
## appealing 1 0.88 0.7658 0.23 1
## satisfying 28 0.87 0.7625 0.24 1
## attractive 3 0.87 0.7591 0.24 1
## lovely 20 0.86 0.7360 0.26 1
## beautiful 5 0.85 0.7302 0.27 1
## pretty 25 0.85 0.7196 0.28 1
## nice 22 0.82 0.6727 0.33 1
## wellDesigned 31 0.81 0.6639 0.34 1
## elegant 11 0.80 0.6454 0.35 1
## harmonious 16 0.80 0.6356 0.36 1
## inviting 18 0.78 0.6007 0.40 1
## fascinating 15 0.77 0.5983 0.40 1
## exciting 14 0.77 0.5939 0.41 1
## engaging 12 0.77 0.5864 0.41 1
## tasteful 30 0.76 0.5750 0.42 1
## sophisticated 29 0.75 0.5642 0.44 1
## interesting 17 0.73 0.5309 0.47 1
## motivating 21 0.71 0.5097 0.49 1
## clean 6 0.71 0.5007 0.50 1
## artistic 2 0.69 0.4813 0.52 1
## professional 26 0.67 0.4544 0.55 1
## balanced 4 0.66 0.4393 0.56 1
## organized 23 0.66 0.4316 0.57 1
## creative 9 0.64 0.4139 0.59 1
## colorHarmonious 8 0.62 0.3830 0.62 1
## provoking 27 0.32 0.1052 0.89 1
## cluttered 7 -0.05 0.0025 1.00 1
##
## PA1
## SS loadings 17.96
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 434 and the objective function was 5.62
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.84 0.04 0.699 0.30 1.0
## pretty 25 0.76 0.39 0.735 0.26 1.5
## delightful 10 0.76 0.44 0.772 0.23 1.6
## creative 9 0.75 0.06 0.571 0.43 1.0
## beautiful 5 0.75 0.42 0.737 0.26 1.6
## fascinating 15 0.74 0.29 0.637 0.36 1.3
## likable 19 0.74 0.49 0.785 0.21 1.7
## pleasing 24 0.74 0.48 0.777 0.22 1.7
## enjoyable 13 0.73 0.49 0.772 0.23 1.7
## lovely 20 0.73 0.46 0.737 0.26 1.7
## exciting 14 0.71 0.33 0.616 0.38 1.4
## nice 22 0.71 0.42 0.676 0.32 1.6
## attractive 3 0.70 0.51 0.758 0.24 1.8
## satisfying 28 0.70 0.52 0.761 0.24 1.9
## appealing 1 0.69 0.53 0.765 0.23 1.9
## interesting 17 0.68 0.30 0.555 0.44 1.4
## engaging 12 0.64 0.42 0.586 0.41 1.7
## inviting 18 0.61 0.48 0.601 0.40 1.9
## elegant 11 0.60 0.54 0.652 0.35 2.0
## motivating 21 0.60 0.39 0.510 0.49 1.7
## tasteful 30 0.59 0.47 0.575 0.42 1.9
## sophisticated 29 0.59 0.47 0.565 0.44 1.9
## harmonious 16 0.58 0.56 0.649 0.35 2.0
## colorHarmonious 8 0.52 0.34 0.383 0.62 1.7
## provoking 27 0.42 -0.02 0.174 0.83 1.0
## organized 23 0.25 0.80 0.701 0.30 1.2
## clean 6 0.36 0.72 0.652 0.35 1.5
## professional 26 0.32 0.72 0.623 0.38 1.4
## balanced 4 0.36 0.64 0.542 0.46 1.6
## wellDesigned 31 0.57 0.61 0.693 0.31 2.0
## cluttered 7 0.09 -0.21 0.054 0.95 1.4
##
## PA1 PA2
## SS loadings 12.35 6.97
## Proportion Var 0.40 0.22
## Cumulative Var 0.40 0.62
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.92
## Multiple R square of scores with factors 0.92 0.85
## Minimum correlation of possible factor scores 0.83 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.01 -0.34 0.699 0.30 1.2
## creative 9 0.90 -0.27 0.571 0.43 1.2
## fascinating 15 0.79 0.02 0.637 0.36 1.0
## pretty 25 0.77 0.13 0.735 0.26 1.1
## delightful 10 0.74 0.19 0.772 0.23 1.1
## beautiful 5 0.74 0.17 0.737 0.26 1.1
## exciting 14 0.74 0.07 0.616 0.38 1.0
## interesting 17 0.71 0.05 0.555 0.44 1.0
## pleasing 24 0.70 0.25 0.777 0.22 1.2
## likable 19 0.70 0.26 0.785 0.21 1.3
## lovely 20 0.70 0.22 0.737 0.26 1.2
## nice 22 0.69 0.19 0.676 0.32 1.1
## enjoyable 13 0.69 0.26 0.772 0.23 1.3
## attractive 3 0.64 0.30 0.758 0.24 1.4
## satisfying 28 0.63 0.32 0.761 0.24 1.5
## appealing 1 0.62 0.33 0.765 0.23 1.5
## engaging 12 0.60 0.22 0.586 0.41 1.3
## motivating 21 0.57 0.19 0.510 0.49 1.2
## inviting 18 0.54 0.30 0.601 0.40 1.6
## tasteful 30 0.53 0.30 0.575 0.42 1.6
## provoking 27 0.52 -0.22 0.174 0.83 1.3
## sophisticated 29 0.52 0.30 0.565 0.44 1.6
## elegant 11 0.51 0.38 0.652 0.35 1.8
## colorHarmonious 8 0.49 0.18 0.383 0.62 1.3
## harmonious 16 0.47 0.42 0.649 0.35 2.0
## organized 23 -0.04 0.87 0.701 0.30 1.0
## professional 26 0.08 0.74 0.623 0.38 1.0
## clean 6 0.13 0.72 0.652 0.35 1.1
## balanced 4 0.16 0.62 0.542 0.46 1.1
## wellDesigned 31 0.43 0.49 0.693 0.31 2.0
## cluttered 7 0.21 -0.30 0.054 0.95 1.8
##
## PA1 PA2
## SS loadings 13.40 5.92
## Proportion Var 0.43 0.19
## Cumulative Var 0.43 0.62
## Proportion Explained 0.69 0.31
## Cumulative Proportion 0.69 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.64
## PA2 0.64 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.96
## Multiple R square of scores with factors 0.97 0.92
## Minimum correlation of possible factor scores 0.94 0.84
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.89 0.7856 0.21 1
## pleasing 24 0.88 0.7768 0.22 1
## enjoyable 13 0.88 0.7728 0.23 1
## delightful 10 0.88 0.7665 0.23 1
## appealing 1 0.88 0.7658 0.23 1
## satisfying 28 0.87 0.7625 0.24 1
## attractive 3 0.87 0.7591 0.24 1
## lovely 20 0.86 0.7360 0.26 1
## beautiful 5 0.85 0.7302 0.27 1
## pretty 25 0.85 0.7196 0.28 1
## nice 22 0.82 0.6727 0.33 1
## wellDesigned 31 0.81 0.6639 0.34 1
## elegant 11 0.80 0.6454 0.35 1
## harmonious 16 0.80 0.6356 0.36 1
## inviting 18 0.78 0.6007 0.40 1
## fascinating 15 0.77 0.5983 0.40 1
## exciting 14 0.77 0.5939 0.41 1
## engaging 12 0.77 0.5864 0.41 1
## tasteful 30 0.76 0.5750 0.42 1
## sophisticated 29 0.75 0.5642 0.44 1
## interesting 17 0.73 0.5309 0.47 1
## motivating 21 0.71 0.5097 0.49 1
## clean 6 0.71 0.5007 0.50 1
## artistic 2 0.69 0.4813 0.52 1
## professional 26 0.67 0.4544 0.55 1
## balanced 4 0.66 0.4393 0.56 1
## organized 23 0.66 0.4316 0.57 1
## creative 9 0.64 0.4139 0.59 1
## colorHarmonious 8 0.62 0.3830 0.62 1
## provoking 27 0.32 0.1052 0.89 1
## cluttered 7 -0.05 0.0025 1.00 1
##
## PA1
## SS loadings 17.96
## Proportion Var 0.58
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 434 and the objective function was 5.62
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.84 0.04 0.699 0.30 1.0
## pretty 25 0.76 0.39 0.735 0.26 1.5
## delightful 10 0.76 0.44 0.772 0.23 1.6
## creative 9 0.75 0.06 0.571 0.43 1.0
## beautiful 5 0.75 0.42 0.737 0.26 1.6
## fascinating 15 0.74 0.29 0.637 0.36 1.3
## likable 19 0.74 0.49 0.785 0.21 1.7
## pleasing 24 0.74 0.48 0.777 0.22 1.7
## enjoyable 13 0.73 0.49 0.772 0.23 1.7
## lovely 20 0.73 0.46 0.737 0.26 1.7
## exciting 14 0.71 0.33 0.616 0.38 1.4
## nice 22 0.71 0.42 0.676 0.32 1.6
## attractive 3 0.70 0.51 0.758 0.24 1.8
## satisfying 28 0.70 0.52 0.761 0.24 1.9
## appealing 1 0.69 0.53 0.765 0.23 1.9
## interesting 17 0.68 0.30 0.555 0.44 1.4
## engaging 12 0.64 0.42 0.586 0.41 1.7
## inviting 18 0.61 0.48 0.601 0.40 1.9
## elegant 11 0.60 0.54 0.652 0.35 2.0
## motivating 21 0.60 0.39 0.510 0.49 1.7
## tasteful 30 0.59 0.47 0.575 0.42 1.9
## sophisticated 29 0.59 0.47 0.565 0.44 1.9
## harmonious 16 0.58 0.56 0.649 0.35 2.0
## colorHarmonious 8 0.52 0.34 0.383 0.62 1.7
## provoking 27 0.42 -0.02 0.174 0.83 1.0
## organized 23 0.25 0.80 0.701 0.30 1.2
## clean 6 0.36 0.72 0.652 0.35 1.5
## professional 26 0.32 0.72 0.623 0.38 1.4
## balanced 4 0.36 0.64 0.542 0.46 1.6
## wellDesigned 31 0.57 0.61 0.693 0.31 2.0
## cluttered 7 0.09 -0.21 0.054 0.95 1.4
##
## PA1 PA2
## SS loadings 12.35 6.97
## Proportion Var 0.40 0.22
## Cumulative Var 0.40 0.62
## Proportion Explained 0.64 0.36
## Cumulative Proportion 0.64 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.92
## Multiple R square of scores with factors 0.92 0.85
## Minimum correlation of possible factor scores 0.83 0.71
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 1.01 -0.34 0.699 0.30 1.2
## creative 9 0.90 -0.27 0.571 0.43 1.2
## fascinating 15 0.79 0.02 0.637 0.36 1.0
## pretty 25 0.77 0.13 0.735 0.26 1.1
## delightful 10 0.74 0.19 0.772 0.23 1.1
## beautiful 5 0.74 0.17 0.737 0.26 1.1
## exciting 14 0.74 0.07 0.616 0.38 1.0
## interesting 17 0.71 0.05 0.555 0.44 1.0
## pleasing 24 0.70 0.25 0.777 0.22 1.2
## likable 19 0.70 0.26 0.785 0.21 1.3
## lovely 20 0.70 0.22 0.737 0.26 1.2
## nice 22 0.69 0.19 0.676 0.32 1.1
## enjoyable 13 0.69 0.26 0.772 0.23 1.3
## attractive 3 0.64 0.30 0.758 0.24 1.4
## satisfying 28 0.63 0.32 0.761 0.24 1.5
## appealing 1 0.62 0.33 0.765 0.23 1.5
## engaging 12 0.60 0.22 0.586 0.41 1.3
## motivating 21 0.57 0.19 0.510 0.49 1.2
## inviting 18 0.54 0.30 0.601 0.40 1.6
## tasteful 30 0.53 0.30 0.575 0.42 1.6
## provoking 27 0.52 -0.22 0.174 0.83 1.3
## sophisticated 29 0.52 0.30 0.565 0.44 1.6
## elegant 11 0.51 0.38 0.652 0.35 1.8
## colorHarmonious 8 0.49 0.18 0.383 0.62 1.3
## harmonious 16 0.47 0.42 0.649 0.35 2.0
## organized 23 -0.04 0.87 0.701 0.30 1.0
## professional 26 0.08 0.74 0.623 0.38 1.0
## clean 6 0.13 0.72 0.652 0.35 1.1
## balanced 4 0.16 0.62 0.542 0.46 1.1
## wellDesigned 31 0.43 0.49 0.693 0.31 2.0
## cluttered 7 0.21 -0.30 0.054 0.95 1.8
##
## PA1 PA2
## SS loadings 13.40 5.92
## Proportion Var 0.43 0.19
## Cumulative Var 0.43 0.62
## Proportion Explained 0.69 0.31
## Cumulative Proportion 0.69 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.64
## PA2 0.64 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 31.16
## The degrees of freedom for the model are 404 and the objective function was 4.21
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.96
## Multiple R square of scores with factors 0.97 0.92
## Minimum correlation of possible factor scores 0.94 0.84
##
##
## ## Image 13
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.89 0.795 0.21 1
## delightful 10 0.89 0.792 0.21 1
## appealing 1 0.88 0.777 0.22 1
## likable 19 0.87 0.759 0.24 1
## pleasing 24 0.87 0.759 0.24 1
## attractive 3 0.86 0.732 0.27 1
## satisfying 28 0.85 0.729 0.27 1
## inviting 18 0.84 0.702 0.30 1
## enjoyable 13 0.83 0.696 0.30 1
## motivating 21 0.83 0.690 0.31 1
## lovely 20 0.83 0.683 0.32 1
## pretty 25 0.83 0.681 0.32 1
## tasteful 30 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.653 0.35 1
## engaging 12 0.80 0.646 0.35 1
## exciting 14 0.79 0.617 0.38 1
## elegant 11 0.78 0.616 0.38 1
## beautiful 5 0.78 0.615 0.38 1
## harmonious 16 0.76 0.582 0.42 1
## fascinating 15 0.76 0.576 0.42 1
## interesting 17 0.74 0.543 0.46 1
## sophisticated 29 0.71 0.503 0.50 1
## balanced 4 0.68 0.463 0.54 1
## professional 26 0.67 0.455 0.54 1
## organized 23 0.65 0.428 0.57 1
## clean 6 0.63 0.391 0.61 1
## creative 9 0.58 0.333 0.67 1
## artistic 2 0.55 0.304 0.70 1
## colorHarmonious 8 0.43 0.184 0.82 1
## provoking 27 0.22 0.049 0.95 1
## cluttered 7 0.12 0.015 0.99 1
##
## PA1
## SS loadings 17.43
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 434 and the objective function was 5.77
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.35 0.751 0.25 1.4
## fascinating 15 0.74 0.30 0.644 0.36 1.3
## exciting 14 0.73 0.36 0.660 0.34 1.5
## lovely 20 0.72 0.42 0.706 0.29 1.6
## nice 22 0.72 0.53 0.799 0.20 1.8
## artistic 2 0.71 0.03 0.505 0.49 1.0
## pleasing 24 0.70 0.52 0.762 0.24 1.8
## interesting 17 0.70 0.32 0.591 0.41 1.4
## beautiful 5 0.70 0.39 0.641 0.36 1.6
## satisfying 28 0.67 0.53 0.728 0.27 1.9
## delightful 10 0.67 0.59 0.790 0.21 2.0
## appealing 1 0.67 0.57 0.775 0.22 2.0
## attractive 3 0.66 0.54 0.731 0.27 1.9
## enjoyable 13 0.66 0.51 0.696 0.30 1.9
## creative 9 0.65 0.13 0.444 0.56 1.1
## likable 19 0.65 0.58 0.758 0.24 2.0
## motivating 21 0.64 0.53 0.688 0.31 1.9
## engaging 12 0.62 0.51 0.645 0.36 1.9
## tasteful 30 0.59 0.56 0.663 0.34 2.0
## sophisticated 29 0.57 0.42 0.505 0.50 1.8
## elegant 11 0.56 0.55 0.618 0.38 2.0
## colorHarmonious 8 0.31 0.29 0.184 0.82 2.0
## provoking 27 0.20 0.11 0.051 0.95 1.5
## organized 23 0.19 0.79 0.660 0.34 1.1
## balanced 4 0.24 0.77 0.654 0.35 1.2
## wellDesigned 31 0.43 0.75 0.740 0.26 1.6
## clean 6 0.22 0.72 0.560 0.44 1.2
## harmonious 16 0.42 0.69 0.647 0.35 1.6
## professional 26 0.32 0.66 0.545 0.46 1.4
## inviting 18 0.56 0.64 0.716 0.28 2.0
## cluttered 7 0.04 0.14 0.020 0.98 1.2
##
## PA1 PA2
## SS loadings 10.62 8.25
## Proportion Var 0.34 0.27
## Cumulative Var 0.34 0.61
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.80 0.75
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.96 -0.41 0.505 0.49 1.3
## pretty 25 0.88 -0.02 0.751 0.25 1.0
## fascinating 15 0.84 -0.05 0.644 0.36 1.0
## creative 9 0.82 -0.23 0.444 0.56 1.2
## exciting 14 0.78 0.04 0.660 0.34 1.0
## interesting 17 0.77 0.00 0.591 0.41 1.0
## lovely 20 0.74 0.13 0.706 0.29 1.1
## beautiful 5 0.72 0.10 0.641 0.36 1.0
## nice 22 0.67 0.27 0.799 0.20 1.3
## pleasing 24 0.65 0.27 0.762 0.24 1.3
## satisfying 28 0.60 0.31 0.728 0.27 1.5
## enjoyable 13 0.59 0.29 0.696 0.30 1.5
## attractive 3 0.58 0.33 0.731 0.27 1.6
## appealing 1 0.57 0.37 0.775 0.22 1.7
## delightful 10 0.56 0.39 0.790 0.21 1.8
## motivating 21 0.55 0.33 0.688 0.31 1.6
## engaging 12 0.53 0.32 0.645 0.36 1.6
## likable 19 0.53 0.40 0.758 0.24 1.8
## sophisticated 29 0.53 0.22 0.505 0.50 1.3
## tasteful 30 0.47 0.40 0.663 0.34 1.9
## elegant 11 0.43 0.41 0.618 0.38 2.0
## colorHarmonious 8 0.25 0.20 0.184 0.82 1.9
## provoking 27 0.21 0.02 0.051 0.95 1.0
## organized 23 -0.22 0.96 0.660 0.34 1.1
## balanced 4 -0.14 0.91 0.654 0.35 1.0
## clean 6 -0.15 0.85 0.560 0.44 1.1
## wellDesigned 31 0.13 0.76 0.740 0.26 1.1
## professional 26 0.03 0.71 0.545 0.46 1.0
## harmonious 16 0.15 0.69 0.647 0.35 1.1
## inviting 18 0.37 0.53 0.716 0.28 1.8
## cluttered 7 -0.03 0.16 0.020 0.98 1.1
##
## PA1 PA2
## SS loadings 11.31 7.56
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.61
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.75
## PA2 0.75 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.95
## Minimum correlation of possible factor scores 0.94 0.90
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.89 0.795 0.21 1
## delightful 10 0.89 0.792 0.21 1
## appealing 1 0.88 0.777 0.22 1
## likable 19 0.87 0.759 0.24 1
## pleasing 24 0.87 0.759 0.24 1
## attractive 3 0.86 0.732 0.27 1
## satisfying 28 0.85 0.729 0.27 1
## inviting 18 0.84 0.702 0.30 1
## enjoyable 13 0.83 0.696 0.30 1
## motivating 21 0.83 0.690 0.31 1
## lovely 20 0.83 0.683 0.32 1
## pretty 25 0.83 0.681 0.32 1
## tasteful 30 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.653 0.35 1
## engaging 12 0.80 0.646 0.35 1
## exciting 14 0.79 0.617 0.38 1
## elegant 11 0.78 0.616 0.38 1
## beautiful 5 0.78 0.615 0.38 1
## harmonious 16 0.76 0.582 0.42 1
## fascinating 15 0.76 0.576 0.42 1
## interesting 17 0.74 0.543 0.46 1
## sophisticated 29 0.71 0.503 0.50 1
## balanced 4 0.68 0.463 0.54 1
## professional 26 0.67 0.455 0.54 1
## organized 23 0.65 0.428 0.57 1
## clean 6 0.63 0.391 0.61 1
## creative 9 0.58 0.333 0.67 1
## artistic 2 0.55 0.304 0.70 1
## colorHarmonious 8 0.43 0.184 0.82 1
## provoking 27 0.22 0.049 0.95 1
## cluttered 7 0.12 0.015 0.99 1
##
## PA1
## SS loadings 17.43
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 434 and the objective function was 5.77
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.35 0.751 0.25 1.4
## fascinating 15 0.74 0.30 0.644 0.36 1.3
## exciting 14 0.73 0.36 0.660 0.34 1.5
## lovely 20 0.72 0.42 0.706 0.29 1.6
## nice 22 0.72 0.53 0.799 0.20 1.8
## artistic 2 0.71 0.03 0.505 0.49 1.0
## pleasing 24 0.70 0.52 0.762 0.24 1.8
## interesting 17 0.70 0.32 0.591 0.41 1.4
## beautiful 5 0.70 0.39 0.641 0.36 1.6
## satisfying 28 0.67 0.53 0.728 0.27 1.9
## delightful 10 0.67 0.59 0.790 0.21 2.0
## appealing 1 0.67 0.57 0.775 0.22 2.0
## attractive 3 0.66 0.54 0.731 0.27 1.9
## enjoyable 13 0.66 0.51 0.696 0.30 1.9
## creative 9 0.65 0.13 0.444 0.56 1.1
## likable 19 0.65 0.58 0.758 0.24 2.0
## motivating 21 0.64 0.53 0.688 0.31 1.9
## engaging 12 0.62 0.51 0.645 0.36 1.9
## tasteful 30 0.59 0.56 0.663 0.34 2.0
## sophisticated 29 0.57 0.42 0.505 0.50 1.8
## elegant 11 0.56 0.55 0.618 0.38 2.0
## colorHarmonious 8 0.31 0.29 0.184 0.82 2.0
## provoking 27 0.20 0.11 0.051 0.95 1.5
## organized 23 0.19 0.79 0.660 0.34 1.1
## balanced 4 0.24 0.77 0.654 0.35 1.2
## wellDesigned 31 0.43 0.75 0.740 0.26 1.6
## clean 6 0.22 0.72 0.560 0.44 1.2
## harmonious 16 0.42 0.69 0.647 0.35 1.6
## professional 26 0.32 0.66 0.545 0.46 1.4
## inviting 18 0.56 0.64 0.716 0.28 2.0
## cluttered 7 0.04 0.14 0.020 0.98 1.2
##
## PA1 PA2
## SS loadings 10.62 8.25
## Proportion Var 0.34 0.27
## Cumulative Var 0.34 0.61
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.80 0.75
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.96 -0.41 0.505 0.49 1.3
## pretty 25 0.88 -0.02 0.751 0.25 1.0
## fascinating 15 0.84 -0.05 0.644 0.36 1.0
## creative 9 0.82 -0.23 0.444 0.56 1.2
## exciting 14 0.78 0.04 0.660 0.34 1.0
## interesting 17 0.77 0.00 0.591 0.41 1.0
## lovely 20 0.74 0.13 0.706 0.29 1.1
## beautiful 5 0.72 0.10 0.641 0.36 1.0
## nice 22 0.67 0.27 0.799 0.20 1.3
## pleasing 24 0.65 0.27 0.762 0.24 1.3
## satisfying 28 0.60 0.31 0.728 0.27 1.5
## enjoyable 13 0.59 0.29 0.696 0.30 1.5
## attractive 3 0.58 0.33 0.731 0.27 1.6
## appealing 1 0.57 0.37 0.775 0.22 1.7
## delightful 10 0.56 0.39 0.790 0.21 1.8
## motivating 21 0.55 0.33 0.688 0.31 1.6
## engaging 12 0.53 0.32 0.645 0.36 1.6
## likable 19 0.53 0.40 0.758 0.24 1.8
## sophisticated 29 0.53 0.22 0.505 0.50 1.3
## tasteful 30 0.47 0.40 0.663 0.34 1.9
## elegant 11 0.43 0.41 0.618 0.38 2.0
## colorHarmonious 8 0.25 0.20 0.184 0.82 1.9
## provoking 27 0.21 0.02 0.051 0.95 1.0
## organized 23 -0.22 0.96 0.660 0.34 1.1
## balanced 4 -0.14 0.91 0.654 0.35 1.0
## clean 6 -0.15 0.85 0.560 0.44 1.1
## wellDesigned 31 0.13 0.76 0.740 0.26 1.1
## professional 26 0.03 0.71 0.545 0.46 1.0
## harmonious 16 0.15 0.69 0.647 0.35 1.1
## inviting 18 0.37 0.53 0.716 0.28 1.8
## cluttered 7 -0.03 0.16 0.020 0.98 1.1
##
## PA1 PA2
## SS loadings 11.31 7.56
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.61
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.75
## PA2 0.75 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.95
## Minimum correlation of possible factor scores 0.94 0.90
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.89 0.795 0.21 1
## delightful 10 0.89 0.792 0.21 1
## appealing 1 0.88 0.777 0.22 1
## likable 19 0.87 0.759 0.24 1
## pleasing 24 0.87 0.759 0.24 1
## attractive 3 0.86 0.732 0.27 1
## satisfying 28 0.85 0.729 0.27 1
## inviting 18 0.84 0.702 0.30 1
## enjoyable 13 0.83 0.696 0.30 1
## motivating 21 0.83 0.690 0.31 1
## lovely 20 0.83 0.683 0.32 1
## pretty 25 0.83 0.681 0.32 1
## tasteful 30 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.653 0.35 1
## engaging 12 0.80 0.646 0.35 1
## exciting 14 0.79 0.617 0.38 1
## elegant 11 0.78 0.616 0.38 1
## beautiful 5 0.78 0.615 0.38 1
## harmonious 16 0.76 0.582 0.42 1
## fascinating 15 0.76 0.576 0.42 1
## interesting 17 0.74 0.543 0.46 1
## sophisticated 29 0.71 0.503 0.50 1
## balanced 4 0.68 0.463 0.54 1
## professional 26 0.67 0.455 0.54 1
## organized 23 0.65 0.428 0.57 1
## clean 6 0.63 0.391 0.61 1
## creative 9 0.58 0.333 0.67 1
## artistic 2 0.55 0.304 0.70 1
## colorHarmonious 8 0.43 0.184 0.82 1
## provoking 27 0.22 0.049 0.95 1
## cluttered 7 0.12 0.015 0.99 1
##
## PA1
## SS loadings 17.43
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 434 and the objective function was 5.77
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.35 0.751 0.25 1.4
## fascinating 15 0.74 0.30 0.644 0.36 1.3
## exciting 14 0.73 0.36 0.660 0.34 1.5
## lovely 20 0.72 0.42 0.706 0.29 1.6
## nice 22 0.72 0.53 0.799 0.20 1.8
## artistic 2 0.71 0.03 0.505 0.49 1.0
## pleasing 24 0.70 0.52 0.762 0.24 1.8
## interesting 17 0.70 0.32 0.591 0.41 1.4
## beautiful 5 0.70 0.39 0.641 0.36 1.6
## satisfying 28 0.67 0.53 0.728 0.27 1.9
## delightful 10 0.67 0.59 0.790 0.21 2.0
## appealing 1 0.67 0.57 0.775 0.22 2.0
## attractive 3 0.66 0.54 0.731 0.27 1.9
## enjoyable 13 0.66 0.51 0.696 0.30 1.9
## creative 9 0.65 0.13 0.444 0.56 1.1
## likable 19 0.65 0.58 0.758 0.24 2.0
## motivating 21 0.64 0.53 0.688 0.31 1.9
## engaging 12 0.62 0.51 0.645 0.36 1.9
## tasteful 30 0.59 0.56 0.663 0.34 2.0
## sophisticated 29 0.57 0.42 0.505 0.50 1.8
## elegant 11 0.56 0.55 0.618 0.38 2.0
## colorHarmonious 8 0.31 0.29 0.184 0.82 2.0
## provoking 27 0.20 0.11 0.051 0.95 1.5
## organized 23 0.19 0.79 0.660 0.34 1.1
## balanced 4 0.24 0.77 0.654 0.35 1.2
## wellDesigned 31 0.43 0.75 0.740 0.26 1.6
## clean 6 0.22 0.72 0.560 0.44 1.2
## harmonious 16 0.42 0.69 0.647 0.35 1.6
## professional 26 0.32 0.66 0.545 0.46 1.4
## inviting 18 0.56 0.64 0.716 0.28 2.0
## cluttered 7 0.04 0.14 0.020 0.98 1.2
##
## PA1 PA2
## SS loadings 10.62 8.25
## Proportion Var 0.34 0.27
## Cumulative Var 0.34 0.61
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.80 0.75
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.96 -0.41 0.505 0.49 1.3
## pretty 25 0.88 -0.02 0.751 0.25 1.0
## fascinating 15 0.84 -0.05 0.644 0.36 1.0
## creative 9 0.82 -0.23 0.444 0.56 1.2
## exciting 14 0.78 0.04 0.660 0.34 1.0
## interesting 17 0.77 0.00 0.591 0.41 1.0
## lovely 20 0.74 0.13 0.706 0.29 1.1
## beautiful 5 0.72 0.10 0.641 0.36 1.0
## nice 22 0.67 0.27 0.799 0.20 1.3
## pleasing 24 0.65 0.27 0.762 0.24 1.3
## satisfying 28 0.60 0.31 0.728 0.27 1.5
## enjoyable 13 0.59 0.29 0.696 0.30 1.5
## attractive 3 0.58 0.33 0.731 0.27 1.6
## appealing 1 0.57 0.37 0.775 0.22 1.7
## delightful 10 0.56 0.39 0.790 0.21 1.8
## motivating 21 0.55 0.33 0.688 0.31 1.6
## engaging 12 0.53 0.32 0.645 0.36 1.6
## likable 19 0.53 0.40 0.758 0.24 1.8
## sophisticated 29 0.53 0.22 0.505 0.50 1.3
## tasteful 30 0.47 0.40 0.663 0.34 1.9
## elegant 11 0.43 0.41 0.618 0.38 2.0
## colorHarmonious 8 0.25 0.20 0.184 0.82 1.9
## provoking 27 0.21 0.02 0.051 0.95 1.0
## organized 23 -0.22 0.96 0.660 0.34 1.1
## balanced 4 -0.14 0.91 0.654 0.35 1.0
## clean 6 -0.15 0.85 0.560 0.44 1.1
## wellDesigned 31 0.13 0.76 0.740 0.26 1.1
## professional 26 0.03 0.71 0.545 0.46 1.0
## harmonious 16 0.15 0.69 0.647 0.35 1.1
## inviting 18 0.37 0.53 0.716 0.28 1.8
## cluttered 7 -0.03 0.16 0.020 0.98 1.1
##
## PA1 PA2
## SS loadings 11.31 7.56
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.61
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.75
## PA2 0.75 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.95
## Minimum correlation of possible factor scores 0.94 0.90
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.89 0.795 0.21 1
## delightful 10 0.89 0.792 0.21 1
## appealing 1 0.88 0.777 0.22 1
## likable 19 0.87 0.759 0.24 1
## pleasing 24 0.87 0.759 0.24 1
## attractive 3 0.86 0.732 0.27 1
## satisfying 28 0.85 0.729 0.27 1
## inviting 18 0.84 0.702 0.30 1
## enjoyable 13 0.83 0.696 0.30 1
## motivating 21 0.83 0.690 0.31 1
## lovely 20 0.83 0.683 0.32 1
## pretty 25 0.83 0.681 0.32 1
## tasteful 30 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.653 0.35 1
## engaging 12 0.80 0.646 0.35 1
## exciting 14 0.79 0.617 0.38 1
## elegant 11 0.78 0.616 0.38 1
## beautiful 5 0.78 0.615 0.38 1
## harmonious 16 0.76 0.582 0.42 1
## fascinating 15 0.76 0.576 0.42 1
## interesting 17 0.74 0.543 0.46 1
## sophisticated 29 0.71 0.503 0.50 1
## balanced 4 0.68 0.463 0.54 1
## professional 26 0.67 0.455 0.54 1
## organized 23 0.65 0.428 0.57 1
## clean 6 0.63 0.391 0.61 1
## creative 9 0.58 0.333 0.67 1
## artistic 2 0.55 0.304 0.70 1
## colorHarmonious 8 0.43 0.184 0.82 1
## provoking 27 0.22 0.049 0.95 1
## cluttered 7 0.12 0.015 0.99 1
##
## PA1
## SS loadings 17.43
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 434 and the objective function was 5.77
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.35 0.751 0.25 1.4
## fascinating 15 0.74 0.30 0.644 0.36 1.3
## exciting 14 0.73 0.36 0.660 0.34 1.5
## lovely 20 0.72 0.42 0.706 0.29 1.6
## nice 22 0.72 0.53 0.799 0.20 1.8
## artistic 2 0.71 0.03 0.505 0.49 1.0
## pleasing 24 0.70 0.52 0.762 0.24 1.8
## interesting 17 0.70 0.32 0.591 0.41 1.4
## beautiful 5 0.70 0.39 0.641 0.36 1.6
## satisfying 28 0.67 0.53 0.728 0.27 1.9
## delightful 10 0.67 0.59 0.790 0.21 2.0
## appealing 1 0.67 0.57 0.775 0.22 2.0
## attractive 3 0.66 0.54 0.731 0.27 1.9
## enjoyable 13 0.66 0.51 0.696 0.30 1.9
## creative 9 0.65 0.13 0.444 0.56 1.1
## likable 19 0.65 0.58 0.758 0.24 2.0
## motivating 21 0.64 0.53 0.688 0.31 1.9
## engaging 12 0.62 0.51 0.645 0.36 1.9
## tasteful 30 0.59 0.56 0.663 0.34 2.0
## sophisticated 29 0.57 0.42 0.505 0.50 1.8
## elegant 11 0.56 0.55 0.618 0.38 2.0
## colorHarmonious 8 0.31 0.29 0.184 0.82 2.0
## provoking 27 0.20 0.11 0.051 0.95 1.5
## organized 23 0.19 0.79 0.660 0.34 1.1
## balanced 4 0.24 0.77 0.654 0.35 1.2
## wellDesigned 31 0.43 0.75 0.740 0.26 1.6
## clean 6 0.22 0.72 0.560 0.44 1.2
## harmonious 16 0.42 0.69 0.647 0.35 1.6
## professional 26 0.32 0.66 0.545 0.46 1.4
## inviting 18 0.56 0.64 0.716 0.28 2.0
## cluttered 7 0.04 0.14 0.020 0.98 1.2
##
## PA1 PA2
## SS loadings 10.62 8.25
## Proportion Var 0.34 0.27
## Cumulative Var 0.34 0.61
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.80 0.75
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.96 -0.41 0.505 0.49 1.3
## pretty 25 0.88 -0.02 0.751 0.25 1.0
## fascinating 15 0.84 -0.05 0.644 0.36 1.0
## creative 9 0.82 -0.23 0.444 0.56 1.2
## exciting 14 0.78 0.04 0.660 0.34 1.0
## interesting 17 0.77 0.00 0.591 0.41 1.0
## lovely 20 0.74 0.13 0.706 0.29 1.1
## beautiful 5 0.72 0.10 0.641 0.36 1.0
## nice 22 0.67 0.27 0.799 0.20 1.3
## pleasing 24 0.65 0.27 0.762 0.24 1.3
## satisfying 28 0.60 0.31 0.728 0.27 1.5
## enjoyable 13 0.59 0.29 0.696 0.30 1.5
## attractive 3 0.58 0.33 0.731 0.27 1.6
## appealing 1 0.57 0.37 0.775 0.22 1.7
## delightful 10 0.56 0.39 0.790 0.21 1.8
## motivating 21 0.55 0.33 0.688 0.31 1.6
## engaging 12 0.53 0.32 0.645 0.36 1.6
## likable 19 0.53 0.40 0.758 0.24 1.8
## sophisticated 29 0.53 0.22 0.505 0.50 1.3
## tasteful 30 0.47 0.40 0.663 0.34 1.9
## elegant 11 0.43 0.41 0.618 0.38 2.0
## colorHarmonious 8 0.25 0.20 0.184 0.82 1.9
## provoking 27 0.21 0.02 0.051 0.95 1.0
## organized 23 -0.22 0.96 0.660 0.34 1.1
## balanced 4 -0.14 0.91 0.654 0.35 1.0
## clean 6 -0.15 0.85 0.560 0.44 1.1
## wellDesigned 31 0.13 0.76 0.740 0.26 1.1
## professional 26 0.03 0.71 0.545 0.46 1.0
## harmonious 16 0.15 0.69 0.647 0.35 1.1
## inviting 18 0.37 0.53 0.716 0.28 1.8
## cluttered 7 -0.03 0.16 0.020 0.98 1.1
##
## PA1 PA2
## SS loadings 11.31 7.56
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.61
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.75
## PA2 0.75 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.95
## Minimum correlation of possible factor scores 0.94 0.90
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## nice 22 0.89 0.795 0.21 1
## delightful 10 0.89 0.792 0.21 1
## appealing 1 0.88 0.777 0.22 1
## likable 19 0.87 0.759 0.24 1
## pleasing 24 0.87 0.759 0.24 1
## attractive 3 0.86 0.732 0.27 1
## satisfying 28 0.85 0.729 0.27 1
## inviting 18 0.84 0.702 0.30 1
## enjoyable 13 0.83 0.696 0.30 1
## motivating 21 0.83 0.690 0.31 1
## lovely 20 0.83 0.683 0.32 1
## pretty 25 0.83 0.681 0.32 1
## tasteful 30 0.81 0.663 0.34 1
## wellDesigned 31 0.81 0.653 0.35 1
## engaging 12 0.80 0.646 0.35 1
## exciting 14 0.79 0.617 0.38 1
## elegant 11 0.78 0.616 0.38 1
## beautiful 5 0.78 0.615 0.38 1
## harmonious 16 0.76 0.582 0.42 1
## fascinating 15 0.76 0.576 0.42 1
## interesting 17 0.74 0.543 0.46 1
## sophisticated 29 0.71 0.503 0.50 1
## balanced 4 0.68 0.463 0.54 1
## professional 26 0.67 0.455 0.54 1
## organized 23 0.65 0.428 0.57 1
## clean 6 0.63 0.391 0.61 1
## creative 9 0.58 0.333 0.67 1
## artistic 2 0.55 0.304 0.70 1
## colorHarmonious 8 0.43 0.184 0.82 1
## provoking 27 0.22 0.049 0.95 1
## cluttered 7 0.12 0.015 0.99 1
##
## PA1
## SS loadings 17.43
## Proportion Var 0.56
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 434 and the objective function was 5.77
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## pretty 25 0.79 0.35 0.751 0.25 1.4
## fascinating 15 0.74 0.30 0.644 0.36 1.3
## exciting 14 0.73 0.36 0.660 0.34 1.5
## lovely 20 0.72 0.42 0.706 0.29 1.6
## nice 22 0.72 0.53 0.799 0.20 1.8
## artistic 2 0.71 0.03 0.505 0.49 1.0
## pleasing 24 0.70 0.52 0.762 0.24 1.8
## interesting 17 0.70 0.32 0.591 0.41 1.4
## beautiful 5 0.70 0.39 0.641 0.36 1.6
## satisfying 28 0.67 0.53 0.728 0.27 1.9
## delightful 10 0.67 0.59 0.790 0.21 2.0
## appealing 1 0.67 0.57 0.775 0.22 2.0
## attractive 3 0.66 0.54 0.731 0.27 1.9
## enjoyable 13 0.66 0.51 0.696 0.30 1.9
## creative 9 0.65 0.13 0.444 0.56 1.1
## likable 19 0.65 0.58 0.758 0.24 2.0
## motivating 21 0.64 0.53 0.688 0.31 1.9
## engaging 12 0.62 0.51 0.645 0.36 1.9
## tasteful 30 0.59 0.56 0.663 0.34 2.0
## sophisticated 29 0.57 0.42 0.505 0.50 1.8
## elegant 11 0.56 0.55 0.618 0.38 2.0
## colorHarmonious 8 0.31 0.29 0.184 0.82 2.0
## provoking 27 0.20 0.11 0.051 0.95 1.5
## organized 23 0.19 0.79 0.660 0.34 1.1
## balanced 4 0.24 0.77 0.654 0.35 1.2
## wellDesigned 31 0.43 0.75 0.740 0.26 1.6
## clean 6 0.22 0.72 0.560 0.44 1.2
## harmonious 16 0.42 0.69 0.647 0.35 1.6
## professional 26 0.32 0.66 0.545 0.46 1.4
## inviting 18 0.56 0.64 0.716 0.28 2.0
## cluttered 7 0.04 0.14 0.020 0.98 1.2
##
## PA1 PA2
## SS loadings 10.62 8.25
## Proportion Var 0.34 0.27
## Cumulative Var 0.34 0.61
## Proportion Explained 0.56 0.44
## Cumulative Proportion 0.56 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.93
## Multiple R square of scores with factors 0.90 0.87
## Minimum correlation of possible factor scores 0.80 0.75
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## artistic 2 0.96 -0.41 0.505 0.49 1.3
## pretty 25 0.88 -0.02 0.751 0.25 1.0
## fascinating 15 0.84 -0.05 0.644 0.36 1.0
## creative 9 0.82 -0.23 0.444 0.56 1.2
## exciting 14 0.78 0.04 0.660 0.34 1.0
## interesting 17 0.77 0.00 0.591 0.41 1.0
## lovely 20 0.74 0.13 0.706 0.29 1.1
## beautiful 5 0.72 0.10 0.641 0.36 1.0
## nice 22 0.67 0.27 0.799 0.20 1.3
## pleasing 24 0.65 0.27 0.762 0.24 1.3
## satisfying 28 0.60 0.31 0.728 0.27 1.5
## enjoyable 13 0.59 0.29 0.696 0.30 1.5
## attractive 3 0.58 0.33 0.731 0.27 1.6
## appealing 1 0.57 0.37 0.775 0.22 1.7
## delightful 10 0.56 0.39 0.790 0.21 1.8
## motivating 21 0.55 0.33 0.688 0.31 1.6
## engaging 12 0.53 0.32 0.645 0.36 1.6
## likable 19 0.53 0.40 0.758 0.24 1.8
## sophisticated 29 0.53 0.22 0.505 0.50 1.3
## tasteful 30 0.47 0.40 0.663 0.34 1.9
## elegant 11 0.43 0.41 0.618 0.38 2.0
## colorHarmonious 8 0.25 0.20 0.184 0.82 1.9
## provoking 27 0.21 0.02 0.051 0.95 1.0
## organized 23 -0.22 0.96 0.660 0.34 1.1
## balanced 4 -0.14 0.91 0.654 0.35 1.0
## clean 6 -0.15 0.85 0.560 0.44 1.1
## wellDesigned 31 0.13 0.76 0.740 0.26 1.1
## professional 26 0.03 0.71 0.545 0.46 1.0
## harmonious 16 0.15 0.69 0.647 0.35 1.1
## inviting 18 0.37 0.53 0.716 0.28 1.8
## cluttered 7 -0.03 0.16 0.020 0.98 1.1
##
## PA1 PA2
## SS loadings 11.31 7.56
## Proportion Var 0.36 0.24
## Cumulative Var 0.36 0.61
## Proportion Explained 0.60 0.40
## Cumulative Proportion 0.60 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.75
## PA2 0.75 1.00
##
## Mean item complexity = 1.3
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 30.41
## The degrees of freedom for the model are 404 and the objective function was 4.11
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.95
## Minimum correlation of possible factor scores 0.94 0.90
##
##
## ## Image 14
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.87 0.7587 0.24 1
## pretty 25 0.86 0.7423 0.26 1
## enjoyable 13 0.85 0.7269 0.27 1
## pleasing 24 0.84 0.7137 0.29 1
## attractive 3 0.84 0.7086 0.29 1
## delightful 10 0.84 0.7038 0.30 1
## appealing 1 0.83 0.6810 0.32 1
## nice 22 0.82 0.6775 0.32 1
## beautiful 5 0.82 0.6655 0.33 1
## satisfying 28 0.81 0.6585 0.34 1
## lovely 20 0.79 0.6310 0.37 1
## tasteful 30 0.77 0.5945 0.41 1
## motivating 21 0.76 0.5810 0.42 1
## inviting 18 0.76 0.5741 0.43 1
## harmonious 16 0.75 0.5699 0.43 1
## exciting 14 0.75 0.5672 0.43 1
## elegant 11 0.74 0.5485 0.45 1
## engaging 12 0.73 0.5393 0.46 1
## clean 6 0.73 0.5376 0.46 1
## balanced 4 0.71 0.5081 0.49 1
## sophisticated 29 0.71 0.5031 0.50 1
## fascinating 15 0.70 0.4908 0.51 1
## wellDesigned 31 0.66 0.4296 0.57 1
## colorHarmonious 8 0.64 0.4133 0.59 1
## organized 23 0.62 0.3901 0.61 1
## professional 26 0.62 0.3845 0.62 1
## interesting 17 0.59 0.3440 0.66 1
## artistic 2 0.58 0.3351 0.66 1
## creative 9 0.54 0.2940 0.71 1
## provoking 27 0.22 0.0492 0.95 1
## cluttered 7 0.05 0.0021 1.00 1
##
## PA1
## SS loadings 16.32
## Proportion Var 0.53
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 434 and the objective function was 5.94
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.80 0.36 0.7767 0.22 1.4
## pleasing 24 0.80 0.38 0.7775 0.22 1.4
## enjoyable 13 0.78 0.41 0.7746 0.23 1.5
## pretty 25 0.78 0.42 0.7839 0.22 1.5
## attractive 3 0.77 0.40 0.7526 0.25 1.5
## lovely 20 0.75 0.35 0.6875 0.31 1.4
## likable 19 0.74 0.48 0.7746 0.23 1.7
## appealing 1 0.73 0.42 0.7085 0.29 1.6
## inviting 18 0.71 0.34 0.6248 0.38 1.4
## beautiful 5 0.71 0.42 0.6899 0.31 1.6
## satisfying 28 0.70 0.43 0.6770 0.32 1.7
## nice 22 0.69 0.47 0.6877 0.31 1.8
## motivating 21 0.64 0.42 0.5922 0.41 1.7
## exciting 14 0.64 0.41 0.5796 0.42 1.7
## tasteful 30 0.59 0.49 0.5932 0.41 1.9
## elegant 11 0.54 0.50 0.5471 0.45 2.0
## provoking 27 0.20 0.10 0.0525 0.95 1.5
## cluttered 7 0.08 -0.02 0.0071 0.99 1.2
## professional 26 0.13 0.81 0.6655 0.33 1.1
## organized 23 0.15 0.79 0.6470 0.35 1.1
## wellDesigned 31 0.21 0.76 0.6228 0.38 1.2
## clean 6 0.35 0.72 0.6387 0.36 1.4
## balanced 4 0.37 0.67 0.5763 0.42 1.6
## fascinating 15 0.41 0.60 0.5219 0.48 1.8
## sophisticated 29 0.43 0.59 0.5269 0.47 1.8
## colorHarmonious 8 0.36 0.56 0.4482 0.55 1.7
## engaging 12 0.48 0.56 0.5480 0.45 2.0
## harmonious 16 0.51 0.56 0.5744 0.43 2.0
## interesting 17 0.32 0.52 0.3751 0.62 1.7
## artistic 2 0.33 0.51 0.3621 0.64 1.7
## creative 9 0.32 0.46 0.3116 0.69 1.8
##
## PA1 PA2
## SS loadings 9.85 8.05
## Proportion Var 0.32 0.26
## Cumulative Var 0.32 0.58
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.88
## Minimum correlation of possible factor scores 0.84 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.86 0.03 0.7767 0.22 1.0
## pleasing 24 0.84 0.05 0.7775 0.22 1.0
## enjoyable 13 0.81 0.10 0.7746 0.23 1.0
## pretty 25 0.80 0.12 0.7839 0.22 1.0
## lovely 20 0.80 0.05 0.6875 0.31 1.0
## attractive 3 0.79 0.10 0.7526 0.25 1.0
## inviting 18 0.76 0.05 0.6248 0.38 1.0
## appealing 1 0.73 0.15 0.7085 0.29 1.1
## likable 19 0.71 0.22 0.7746 0.23 1.2
## beautiful 5 0.71 0.16 0.6899 0.31 1.1
## satisfying 28 0.69 0.18 0.6770 0.32 1.1
## nice 22 0.65 0.23 0.6877 0.31 1.2
## exciting 14 0.62 0.18 0.5796 0.42 1.2
## motivating 21 0.62 0.20 0.5922 0.41 1.2
## tasteful 30 0.51 0.32 0.5932 0.41 1.7
## elegant 11 0.44 0.35 0.5471 0.45 1.9
## provoking 27 0.21 0.02 0.0525 0.95 1.0
## cluttered 7 0.12 -0.07 0.0071 0.99 1.7
## professional 26 -0.26 0.98 0.6655 0.33 1.1
## organized 23 -0.23 0.95 0.6470 0.35 1.1
## wellDesigned 31 -0.13 0.87 0.6228 0.38 1.0
## clean 6 0.07 0.75 0.6387 0.36 1.0
## balanced 4 0.12 0.67 0.5763 0.42 1.1
## fascinating 15 0.22 0.55 0.5219 0.48 1.3
## colorHarmonious 8 0.17 0.54 0.4482 0.55 1.2
## sophisticated 29 0.25 0.53 0.5269 0.47 1.4
## interesting 17 0.15 0.50 0.3751 0.62 1.2
## artistic 2 0.16 0.48 0.3621 0.64 1.2
## engaging 12 0.34 0.46 0.5480 0.45 1.8
## harmonious 16 0.38 0.44 0.5744 0.43 2.0
## creative 9 0.17 0.42 0.3116 0.69 1.3
##
## PA1 PA2
## SS loadings 10.36 7.54
## Proportion Var 0.33 0.24
## Cumulative Var 0.33 0.58
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.87 0.7587 0.24 1
## pretty 25 0.86 0.7423 0.26 1
## enjoyable 13 0.85 0.7269 0.27 1
## pleasing 24 0.84 0.7137 0.29 1
## attractive 3 0.84 0.7086 0.29 1
## delightful 10 0.84 0.7038 0.30 1
## appealing 1 0.83 0.6810 0.32 1
## nice 22 0.82 0.6775 0.32 1
## beautiful 5 0.82 0.6655 0.33 1
## satisfying 28 0.81 0.6585 0.34 1
## lovely 20 0.79 0.6310 0.37 1
## tasteful 30 0.77 0.5945 0.41 1
## motivating 21 0.76 0.5810 0.42 1
## inviting 18 0.76 0.5741 0.43 1
## harmonious 16 0.75 0.5699 0.43 1
## exciting 14 0.75 0.5672 0.43 1
## elegant 11 0.74 0.5485 0.45 1
## engaging 12 0.73 0.5393 0.46 1
## clean 6 0.73 0.5376 0.46 1
## balanced 4 0.71 0.5081 0.49 1
## sophisticated 29 0.71 0.5031 0.50 1
## fascinating 15 0.70 0.4908 0.51 1
## wellDesigned 31 0.66 0.4296 0.57 1
## colorHarmonious 8 0.64 0.4133 0.59 1
## organized 23 0.62 0.3901 0.61 1
## professional 26 0.62 0.3845 0.62 1
## interesting 17 0.59 0.3440 0.66 1
## artistic 2 0.58 0.3351 0.66 1
## creative 9 0.54 0.2940 0.71 1
## provoking 27 0.22 0.0492 0.95 1
## cluttered 7 0.05 0.0021 1.00 1
##
## PA1
## SS loadings 16.32
## Proportion Var 0.53
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 434 and the objective function was 5.94
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.80 0.36 0.7767 0.22 1.4
## pleasing 24 0.80 0.38 0.7775 0.22 1.4
## enjoyable 13 0.78 0.41 0.7746 0.23 1.5
## pretty 25 0.78 0.42 0.7839 0.22 1.5
## attractive 3 0.77 0.40 0.7526 0.25 1.5
## lovely 20 0.75 0.35 0.6875 0.31 1.4
## likable 19 0.74 0.48 0.7746 0.23 1.7
## appealing 1 0.73 0.42 0.7085 0.29 1.6
## inviting 18 0.71 0.34 0.6248 0.38 1.4
## beautiful 5 0.71 0.42 0.6899 0.31 1.6
## satisfying 28 0.70 0.43 0.6770 0.32 1.7
## nice 22 0.69 0.47 0.6877 0.31 1.8
## motivating 21 0.64 0.42 0.5922 0.41 1.7
## exciting 14 0.64 0.41 0.5796 0.42 1.7
## tasteful 30 0.59 0.49 0.5932 0.41 1.9
## elegant 11 0.54 0.50 0.5471 0.45 2.0
## provoking 27 0.20 0.10 0.0525 0.95 1.5
## cluttered 7 0.08 -0.02 0.0071 0.99 1.2
## professional 26 0.13 0.81 0.6655 0.33 1.1
## organized 23 0.15 0.79 0.6470 0.35 1.1
## wellDesigned 31 0.21 0.76 0.6228 0.38 1.2
## clean 6 0.35 0.72 0.6387 0.36 1.4
## balanced 4 0.37 0.67 0.5763 0.42 1.6
## fascinating 15 0.41 0.60 0.5219 0.48 1.8
## sophisticated 29 0.43 0.59 0.5269 0.47 1.8
## colorHarmonious 8 0.36 0.56 0.4482 0.55 1.7
## engaging 12 0.48 0.56 0.5480 0.45 2.0
## harmonious 16 0.51 0.56 0.5744 0.43 2.0
## interesting 17 0.32 0.52 0.3751 0.62 1.7
## artistic 2 0.33 0.51 0.3621 0.64 1.7
## creative 9 0.32 0.46 0.3116 0.69 1.8
##
## PA1 PA2
## SS loadings 9.85 8.05
## Proportion Var 0.32 0.26
## Cumulative Var 0.32 0.58
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.88
## Minimum correlation of possible factor scores 0.84 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.86 0.03 0.7767 0.22 1.0
## pleasing 24 0.84 0.05 0.7775 0.22 1.0
## enjoyable 13 0.81 0.10 0.7746 0.23 1.0
## pretty 25 0.80 0.12 0.7839 0.22 1.0
## lovely 20 0.80 0.05 0.6875 0.31 1.0
## attractive 3 0.79 0.10 0.7526 0.25 1.0
## inviting 18 0.76 0.05 0.6248 0.38 1.0
## appealing 1 0.73 0.15 0.7085 0.29 1.1
## likable 19 0.71 0.22 0.7746 0.23 1.2
## beautiful 5 0.71 0.16 0.6899 0.31 1.1
## satisfying 28 0.69 0.18 0.6770 0.32 1.1
## nice 22 0.65 0.23 0.6877 0.31 1.2
## exciting 14 0.62 0.18 0.5796 0.42 1.2
## motivating 21 0.62 0.20 0.5922 0.41 1.2
## tasteful 30 0.51 0.32 0.5932 0.41 1.7
## elegant 11 0.44 0.35 0.5471 0.45 1.9
## provoking 27 0.21 0.02 0.0525 0.95 1.0
## cluttered 7 0.12 -0.07 0.0071 0.99 1.7
## professional 26 -0.26 0.98 0.6655 0.33 1.1
## organized 23 -0.23 0.95 0.6470 0.35 1.1
## wellDesigned 31 -0.13 0.87 0.6228 0.38 1.0
## clean 6 0.07 0.75 0.6387 0.36 1.0
## balanced 4 0.12 0.67 0.5763 0.42 1.1
## fascinating 15 0.22 0.55 0.5219 0.48 1.3
## colorHarmonious 8 0.17 0.54 0.4482 0.55 1.2
## sophisticated 29 0.25 0.53 0.5269 0.47 1.4
## interesting 17 0.15 0.50 0.3751 0.62 1.2
## artistic 2 0.16 0.48 0.3621 0.64 1.2
## engaging 12 0.34 0.46 0.5480 0.45 1.8
## harmonious 16 0.38 0.44 0.5744 0.43 2.0
## creative 9 0.17 0.42 0.3116 0.69 1.3
##
## PA1 PA2
## SS loadings 10.36 7.54
## Proportion Var 0.33 0.24
## Cumulative Var 0.33 0.58
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.87 0.7587 0.24 1
## pretty 25 0.86 0.7423 0.26 1
## enjoyable 13 0.85 0.7269 0.27 1
## pleasing 24 0.84 0.7137 0.29 1
## attractive 3 0.84 0.7086 0.29 1
## delightful 10 0.84 0.7038 0.30 1
## appealing 1 0.83 0.6810 0.32 1
## nice 22 0.82 0.6775 0.32 1
## beautiful 5 0.82 0.6655 0.33 1
## satisfying 28 0.81 0.6585 0.34 1
## lovely 20 0.79 0.6310 0.37 1
## tasteful 30 0.77 0.5945 0.41 1
## motivating 21 0.76 0.5810 0.42 1
## inviting 18 0.76 0.5741 0.43 1
## harmonious 16 0.75 0.5699 0.43 1
## exciting 14 0.75 0.5672 0.43 1
## elegant 11 0.74 0.5485 0.45 1
## engaging 12 0.73 0.5393 0.46 1
## clean 6 0.73 0.5376 0.46 1
## balanced 4 0.71 0.5081 0.49 1
## sophisticated 29 0.71 0.5031 0.50 1
## fascinating 15 0.70 0.4908 0.51 1
## wellDesigned 31 0.66 0.4296 0.57 1
## colorHarmonious 8 0.64 0.4133 0.59 1
## organized 23 0.62 0.3901 0.61 1
## professional 26 0.62 0.3845 0.62 1
## interesting 17 0.59 0.3440 0.66 1
## artistic 2 0.58 0.3351 0.66 1
## creative 9 0.54 0.2940 0.71 1
## provoking 27 0.22 0.0492 0.95 1
## cluttered 7 0.05 0.0021 1.00 1
##
## PA1
## SS loadings 16.32
## Proportion Var 0.53
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 434 and the objective function was 5.94
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.80 0.36 0.7767 0.22 1.4
## pleasing 24 0.80 0.38 0.7775 0.22 1.4
## enjoyable 13 0.78 0.41 0.7746 0.23 1.5
## pretty 25 0.78 0.42 0.7839 0.22 1.5
## attractive 3 0.77 0.40 0.7526 0.25 1.5
## lovely 20 0.75 0.35 0.6875 0.31 1.4
## likable 19 0.74 0.48 0.7746 0.23 1.7
## appealing 1 0.73 0.42 0.7085 0.29 1.6
## inviting 18 0.71 0.34 0.6248 0.38 1.4
## beautiful 5 0.71 0.42 0.6899 0.31 1.6
## satisfying 28 0.70 0.43 0.6770 0.32 1.7
## nice 22 0.69 0.47 0.6877 0.31 1.8
## motivating 21 0.64 0.42 0.5922 0.41 1.7
## exciting 14 0.64 0.41 0.5796 0.42 1.7
## tasteful 30 0.59 0.49 0.5932 0.41 1.9
## elegant 11 0.54 0.50 0.5471 0.45 2.0
## provoking 27 0.20 0.10 0.0525 0.95 1.5
## cluttered 7 0.08 -0.02 0.0071 0.99 1.2
## professional 26 0.13 0.81 0.6655 0.33 1.1
## organized 23 0.15 0.79 0.6470 0.35 1.1
## wellDesigned 31 0.21 0.76 0.6228 0.38 1.2
## clean 6 0.35 0.72 0.6387 0.36 1.4
## balanced 4 0.37 0.67 0.5763 0.42 1.6
## fascinating 15 0.41 0.60 0.5219 0.48 1.8
## sophisticated 29 0.43 0.59 0.5269 0.47 1.8
## colorHarmonious 8 0.36 0.56 0.4482 0.55 1.7
## engaging 12 0.48 0.56 0.5480 0.45 2.0
## harmonious 16 0.51 0.56 0.5744 0.43 2.0
## interesting 17 0.32 0.52 0.3751 0.62 1.7
## artistic 2 0.33 0.51 0.3621 0.64 1.7
## creative 9 0.32 0.46 0.3116 0.69 1.8
##
## PA1 PA2
## SS loadings 9.85 8.05
## Proportion Var 0.32 0.26
## Cumulative Var 0.32 0.58
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.88
## Minimum correlation of possible factor scores 0.84 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.86 0.03 0.7767 0.22 1.0
## pleasing 24 0.84 0.05 0.7775 0.22 1.0
## enjoyable 13 0.81 0.10 0.7746 0.23 1.0
## pretty 25 0.80 0.12 0.7839 0.22 1.0
## lovely 20 0.80 0.05 0.6875 0.31 1.0
## attractive 3 0.79 0.10 0.7526 0.25 1.0
## inviting 18 0.76 0.05 0.6248 0.38 1.0
## appealing 1 0.73 0.15 0.7085 0.29 1.1
## likable 19 0.71 0.22 0.7746 0.23 1.2
## beautiful 5 0.71 0.16 0.6899 0.31 1.1
## satisfying 28 0.69 0.18 0.6770 0.32 1.1
## nice 22 0.65 0.23 0.6877 0.31 1.2
## exciting 14 0.62 0.18 0.5796 0.42 1.2
## motivating 21 0.62 0.20 0.5922 0.41 1.2
## tasteful 30 0.51 0.32 0.5932 0.41 1.7
## elegant 11 0.44 0.35 0.5471 0.45 1.9
## provoking 27 0.21 0.02 0.0525 0.95 1.0
## cluttered 7 0.12 -0.07 0.0071 0.99 1.7
## professional 26 -0.26 0.98 0.6655 0.33 1.1
## organized 23 -0.23 0.95 0.6470 0.35 1.1
## wellDesigned 31 -0.13 0.87 0.6228 0.38 1.0
## clean 6 0.07 0.75 0.6387 0.36 1.0
## balanced 4 0.12 0.67 0.5763 0.42 1.1
## fascinating 15 0.22 0.55 0.5219 0.48 1.3
## colorHarmonious 8 0.17 0.54 0.4482 0.55 1.2
## sophisticated 29 0.25 0.53 0.5269 0.47 1.4
## interesting 17 0.15 0.50 0.3751 0.62 1.2
## artistic 2 0.16 0.48 0.3621 0.64 1.2
## engaging 12 0.34 0.46 0.5480 0.45 1.8
## harmonious 16 0.38 0.44 0.5744 0.43 2.0
## creative 9 0.17 0.42 0.3116 0.69 1.3
##
## PA1 PA2
## SS loadings 10.36 7.54
## Proportion Var 0.33 0.24
## Cumulative Var 0.33 0.58
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.87 0.7587 0.24 1
## pretty 25 0.86 0.7423 0.26 1
## enjoyable 13 0.85 0.7269 0.27 1
## pleasing 24 0.84 0.7137 0.29 1
## attractive 3 0.84 0.7086 0.29 1
## delightful 10 0.84 0.7038 0.30 1
## appealing 1 0.83 0.6810 0.32 1
## nice 22 0.82 0.6775 0.32 1
## beautiful 5 0.82 0.6655 0.33 1
## satisfying 28 0.81 0.6585 0.34 1
## lovely 20 0.79 0.6310 0.37 1
## tasteful 30 0.77 0.5945 0.41 1
## motivating 21 0.76 0.5810 0.42 1
## inviting 18 0.76 0.5741 0.43 1
## harmonious 16 0.75 0.5699 0.43 1
## exciting 14 0.75 0.5672 0.43 1
## elegant 11 0.74 0.5485 0.45 1
## engaging 12 0.73 0.5393 0.46 1
## clean 6 0.73 0.5376 0.46 1
## balanced 4 0.71 0.5081 0.49 1
## sophisticated 29 0.71 0.5031 0.50 1
## fascinating 15 0.70 0.4908 0.51 1
## wellDesigned 31 0.66 0.4296 0.57 1
## colorHarmonious 8 0.64 0.4133 0.59 1
## organized 23 0.62 0.3901 0.61 1
## professional 26 0.62 0.3845 0.62 1
## interesting 17 0.59 0.3440 0.66 1
## artistic 2 0.58 0.3351 0.66 1
## creative 9 0.54 0.2940 0.71 1
## provoking 27 0.22 0.0492 0.95 1
## cluttered 7 0.05 0.0021 1.00 1
##
## PA1
## SS loadings 16.32
## Proportion Var 0.53
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 434 and the objective function was 5.94
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.80 0.36 0.7767 0.22 1.4
## pleasing 24 0.80 0.38 0.7775 0.22 1.4
## enjoyable 13 0.78 0.41 0.7746 0.23 1.5
## pretty 25 0.78 0.42 0.7839 0.22 1.5
## attractive 3 0.77 0.40 0.7526 0.25 1.5
## lovely 20 0.75 0.35 0.6875 0.31 1.4
## likable 19 0.74 0.48 0.7746 0.23 1.7
## appealing 1 0.73 0.42 0.7085 0.29 1.6
## inviting 18 0.71 0.34 0.6248 0.38 1.4
## beautiful 5 0.71 0.42 0.6899 0.31 1.6
## satisfying 28 0.70 0.43 0.6770 0.32 1.7
## nice 22 0.69 0.47 0.6877 0.31 1.8
## motivating 21 0.64 0.42 0.5922 0.41 1.7
## exciting 14 0.64 0.41 0.5796 0.42 1.7
## tasteful 30 0.59 0.49 0.5932 0.41 1.9
## elegant 11 0.54 0.50 0.5471 0.45 2.0
## provoking 27 0.20 0.10 0.0525 0.95 1.5
## cluttered 7 0.08 -0.02 0.0071 0.99 1.2
## professional 26 0.13 0.81 0.6655 0.33 1.1
## organized 23 0.15 0.79 0.6470 0.35 1.1
## wellDesigned 31 0.21 0.76 0.6228 0.38 1.2
## clean 6 0.35 0.72 0.6387 0.36 1.4
## balanced 4 0.37 0.67 0.5763 0.42 1.6
## fascinating 15 0.41 0.60 0.5219 0.48 1.8
## sophisticated 29 0.43 0.59 0.5269 0.47 1.8
## colorHarmonious 8 0.36 0.56 0.4482 0.55 1.7
## engaging 12 0.48 0.56 0.5480 0.45 2.0
## harmonious 16 0.51 0.56 0.5744 0.43 2.0
## interesting 17 0.32 0.52 0.3751 0.62 1.7
## artistic 2 0.33 0.51 0.3621 0.64 1.7
## creative 9 0.32 0.46 0.3116 0.69 1.8
##
## PA1 PA2
## SS loadings 9.85 8.05
## Proportion Var 0.32 0.26
## Cumulative Var 0.32 0.58
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.88
## Minimum correlation of possible factor scores 0.84 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.86 0.03 0.7767 0.22 1.0
## pleasing 24 0.84 0.05 0.7775 0.22 1.0
## enjoyable 13 0.81 0.10 0.7746 0.23 1.0
## pretty 25 0.80 0.12 0.7839 0.22 1.0
## lovely 20 0.80 0.05 0.6875 0.31 1.0
## attractive 3 0.79 0.10 0.7526 0.25 1.0
## inviting 18 0.76 0.05 0.6248 0.38 1.0
## appealing 1 0.73 0.15 0.7085 0.29 1.1
## likable 19 0.71 0.22 0.7746 0.23 1.2
## beautiful 5 0.71 0.16 0.6899 0.31 1.1
## satisfying 28 0.69 0.18 0.6770 0.32 1.1
## nice 22 0.65 0.23 0.6877 0.31 1.2
## exciting 14 0.62 0.18 0.5796 0.42 1.2
## motivating 21 0.62 0.20 0.5922 0.41 1.2
## tasteful 30 0.51 0.32 0.5932 0.41 1.7
## elegant 11 0.44 0.35 0.5471 0.45 1.9
## provoking 27 0.21 0.02 0.0525 0.95 1.0
## cluttered 7 0.12 -0.07 0.0071 0.99 1.7
## professional 26 -0.26 0.98 0.6655 0.33 1.1
## organized 23 -0.23 0.95 0.6470 0.35 1.1
## wellDesigned 31 -0.13 0.87 0.6228 0.38 1.0
## clean 6 0.07 0.75 0.6387 0.36 1.0
## balanced 4 0.12 0.67 0.5763 0.42 1.1
## fascinating 15 0.22 0.55 0.5219 0.48 1.3
## colorHarmonious 8 0.17 0.54 0.4482 0.55 1.2
## sophisticated 29 0.25 0.53 0.5269 0.47 1.4
## interesting 17 0.15 0.50 0.3751 0.62 1.2
## artistic 2 0.16 0.48 0.3621 0.64 1.2
## engaging 12 0.34 0.46 0.5480 0.45 1.8
## harmonious 16 0.38 0.44 0.5744 0.43 2.0
## creative 9 0.17 0.42 0.3116 0.69 1.3
##
## PA1 PA2
## SS loadings 10.36 7.54
## Proportion Var 0.33 0.24
## Cumulative Var 0.33 0.58
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## likable 19 0.87 0.7587 0.24 1
## pretty 25 0.86 0.7423 0.26 1
## enjoyable 13 0.85 0.7269 0.27 1
## pleasing 24 0.84 0.7137 0.29 1
## attractive 3 0.84 0.7086 0.29 1
## delightful 10 0.84 0.7038 0.30 1
## appealing 1 0.83 0.6810 0.32 1
## nice 22 0.82 0.6775 0.32 1
## beautiful 5 0.82 0.6655 0.33 1
## satisfying 28 0.81 0.6585 0.34 1
## lovely 20 0.79 0.6310 0.37 1
## tasteful 30 0.77 0.5945 0.41 1
## motivating 21 0.76 0.5810 0.42 1
## inviting 18 0.76 0.5741 0.43 1
## harmonious 16 0.75 0.5699 0.43 1
## exciting 14 0.75 0.5672 0.43 1
## elegant 11 0.74 0.5485 0.45 1
## engaging 12 0.73 0.5393 0.46 1
## clean 6 0.73 0.5376 0.46 1
## balanced 4 0.71 0.5081 0.49 1
## sophisticated 29 0.71 0.5031 0.50 1
## fascinating 15 0.70 0.4908 0.51 1
## wellDesigned 31 0.66 0.4296 0.57 1
## colorHarmonious 8 0.64 0.4133 0.59 1
## organized 23 0.62 0.3901 0.61 1
## professional 26 0.62 0.3845 0.62 1
## interesting 17 0.59 0.3440 0.66 1
## artistic 2 0.58 0.3351 0.66 1
## creative 9 0.54 0.2940 0.71 1
## provoking 27 0.22 0.0492 0.95 1
## cluttered 7 0.05 0.0021 1.00 1
##
## PA1
## SS loadings 16.32
## Proportion Var 0.53
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 434 and the objective function was 5.94
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.07
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.95
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.80 0.36 0.7767 0.22 1.4
## pleasing 24 0.80 0.38 0.7775 0.22 1.4
## enjoyable 13 0.78 0.41 0.7746 0.23 1.5
## pretty 25 0.78 0.42 0.7839 0.22 1.5
## attractive 3 0.77 0.40 0.7526 0.25 1.5
## lovely 20 0.75 0.35 0.6875 0.31 1.4
## likable 19 0.74 0.48 0.7746 0.23 1.7
## appealing 1 0.73 0.42 0.7085 0.29 1.6
## inviting 18 0.71 0.34 0.6248 0.38 1.4
## beautiful 5 0.71 0.42 0.6899 0.31 1.6
## satisfying 28 0.70 0.43 0.6770 0.32 1.7
## nice 22 0.69 0.47 0.6877 0.31 1.8
## motivating 21 0.64 0.42 0.5922 0.41 1.7
## exciting 14 0.64 0.41 0.5796 0.42 1.7
## tasteful 30 0.59 0.49 0.5932 0.41 1.9
## elegant 11 0.54 0.50 0.5471 0.45 2.0
## provoking 27 0.20 0.10 0.0525 0.95 1.5
## cluttered 7 0.08 -0.02 0.0071 0.99 1.2
## professional 26 0.13 0.81 0.6655 0.33 1.1
## organized 23 0.15 0.79 0.6470 0.35 1.1
## wellDesigned 31 0.21 0.76 0.6228 0.38 1.2
## clean 6 0.35 0.72 0.6387 0.36 1.4
## balanced 4 0.37 0.67 0.5763 0.42 1.6
## fascinating 15 0.41 0.60 0.5219 0.48 1.8
## sophisticated 29 0.43 0.59 0.5269 0.47 1.8
## colorHarmonious 8 0.36 0.56 0.4482 0.55 1.7
## engaging 12 0.48 0.56 0.5480 0.45 2.0
## harmonious 16 0.51 0.56 0.5744 0.43 2.0
## interesting 17 0.32 0.52 0.3751 0.62 1.7
## artistic 2 0.33 0.51 0.3621 0.64 1.7
## creative 9 0.32 0.46 0.3116 0.69 1.8
##
## PA1 PA2
## SS loadings 9.85 8.05
## Proportion Var 0.32 0.26
## Cumulative Var 0.32 0.58
## Proportion Explained 0.55 0.45
## Cumulative Proportion 0.55 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.96 0.94
## Multiple R square of scores with factors 0.92 0.88
## Minimum correlation of possible factor scores 0.84 0.76
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## delightful 10 0.86 0.03 0.7767 0.22 1.0
## pleasing 24 0.84 0.05 0.7775 0.22 1.0
## enjoyable 13 0.81 0.10 0.7746 0.23 1.0
## pretty 25 0.80 0.12 0.7839 0.22 1.0
## lovely 20 0.80 0.05 0.6875 0.31 1.0
## attractive 3 0.79 0.10 0.7526 0.25 1.0
## inviting 18 0.76 0.05 0.6248 0.38 1.0
## appealing 1 0.73 0.15 0.7085 0.29 1.1
## likable 19 0.71 0.22 0.7746 0.23 1.2
## beautiful 5 0.71 0.16 0.6899 0.31 1.1
## satisfying 28 0.69 0.18 0.6770 0.32 1.1
## nice 22 0.65 0.23 0.6877 0.31 1.2
## exciting 14 0.62 0.18 0.5796 0.42 1.2
## motivating 21 0.62 0.20 0.5922 0.41 1.2
## tasteful 30 0.51 0.32 0.5932 0.41 1.7
## elegant 11 0.44 0.35 0.5471 0.45 1.9
## provoking 27 0.21 0.02 0.0525 0.95 1.0
## cluttered 7 0.12 -0.07 0.0071 0.99 1.7
## professional 26 -0.26 0.98 0.6655 0.33 1.1
## organized 23 -0.23 0.95 0.6470 0.35 1.1
## wellDesigned 31 -0.13 0.87 0.6228 0.38 1.0
## clean 6 0.07 0.75 0.6387 0.36 1.0
## balanced 4 0.12 0.67 0.5763 0.42 1.1
## fascinating 15 0.22 0.55 0.5219 0.48 1.3
## colorHarmonious 8 0.17 0.54 0.4482 0.55 1.2
## sophisticated 29 0.25 0.53 0.5269 0.47 1.4
## interesting 17 0.15 0.50 0.3751 0.62 1.2
## artistic 2 0.16 0.48 0.3621 0.64 1.2
## engaging 12 0.34 0.46 0.5480 0.45 1.8
## harmonious 16 0.38 0.44 0.5744 0.43 2.0
## creative 9 0.17 0.42 0.3116 0.69 1.3
##
## PA1 PA2
## SS loadings 10.36 7.54
## Proportion Var 0.33 0.24
## Cumulative Var 0.33 0.58
## Proportion Explained 0.58 0.42
## Cumulative Proportion 0.58 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.71
## PA2 0.71 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 27.59
## The degrees of freedom for the model are 404 and the objective function was 3.9
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.97
## Multiple R square of scores with factors 0.97 0.94
## Minimum correlation of possible factor scores 0.94 0.88
##
##
## ## Image 15
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.90 0.813 0.19 1
## nice 22 0.89 0.795 0.20 1
## likable 19 0.89 0.794 0.21 1
## enjoyable 13 0.89 0.789 0.21 1
## delightful 10 0.88 0.781 0.22 1
## pleasing 24 0.88 0.771 0.23 1
## pretty 25 0.85 0.726 0.27 1
## attractive 3 0.85 0.722 0.28 1
## satisfying 28 0.84 0.705 0.29 1
## beautiful 5 0.84 0.703 0.30 1
## inviting 18 0.83 0.687 0.31 1
## tasteful 30 0.83 0.684 0.32 1
## lovely 20 0.83 0.682 0.32 1
## harmonious 16 0.81 0.652 0.35 1
## engaging 12 0.80 0.647 0.35 1
## elegant 11 0.80 0.633 0.37 1
## exciting 14 0.79 0.622 0.38 1
## motivating 21 0.77 0.588 0.41 1
## wellDesigned 31 0.76 0.582 0.42 1
## interesting 17 0.74 0.543 0.46 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.71 0.501 0.50 1
## sophisticated 29 0.71 0.500 0.50 1
## clean 6 0.67 0.449 0.55 1
## artistic 2 0.67 0.443 0.56 1
## organized 23 0.65 0.426 0.57 1
## creative 9 0.65 0.418 0.58 1
## colorHarmonious 8 0.64 0.406 0.59 1
## professional 26 0.60 0.355 0.64 1
## provoking 27 0.35 0.126 0.87 1
## cluttered 7 0.24 0.056 0.94 1
##
## PA1
## SS loadings 18.14
## Proportion Var 0.59
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 434 and the objective function was 6.31
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.83 0.10 0.691 0.31 1.0
## balanced 4 0.76 0.28 0.656 0.34 1.3
## harmonious 16 0.76 0.38 0.719 0.28 1.5
## clean 6 0.75 0.20 0.601 0.40 1.1
## wellDesigned 31 0.72 0.36 0.645 0.36 1.5
## appealing 1 0.68 0.59 0.813 0.19 2.0
## satisfying 28 0.68 0.51 0.716 0.28 1.9
## pleasing 24 0.67 0.57 0.773 0.23 2.0
## nice 22 0.67 0.59 0.795 0.21 2.0
## professional 26 0.66 0.18 0.468 0.53 1.1
## delightful 10 0.66 0.59 0.780 0.22 2.0
## elegant 11 0.64 0.48 0.643 0.36 1.8
## likable 19 0.63 0.63 0.792 0.21 2.0
## lovely 20 0.58 0.58 0.681 0.32 2.0
## colorHarmonious 8 0.49 0.41 0.407 0.59 1.9
## cluttered 7 0.24 0.09 0.067 0.93 1.3
## creative 9 0.19 0.74 0.584 0.42 1.1
## fascinating 15 0.28 0.74 0.621 0.38 1.3
## artistic 2 0.26 0.69 0.546 0.45 1.3
## interesting 17 0.37 0.68 0.602 0.40 1.5
## exciting 14 0.44 0.68 0.657 0.34 1.7
## attractive 3 0.54 0.66 0.730 0.27 1.9
## enjoyable 13 0.60 0.65 0.790 0.21 2.0
## engaging 12 0.49 0.65 0.662 0.34 1.9
## beautiful 5 0.54 0.65 0.710 0.29 1.9
## pretty 25 0.57 0.64 0.729 0.27 2.0
## tasteful 30 0.53 0.64 0.691 0.31 1.9
## inviting 18 0.56 0.61 0.687 0.31 2.0
## motivating 21 0.48 0.61 0.597 0.40 1.9
## provoking 27 -0.04 0.56 0.315 0.69 1.0
## sophisticated 29 0.45 0.55 0.506 0.49 1.9
##
## PA1 PA2
## SS loadings 10.11 9.57
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.79 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 1.06 -0.36 0.691 0.31 1.2
## clean 6 0.90 -0.18 0.601 0.40 1.1
## balanced 4 0.86 -0.07 0.656 0.34 1.0
## harmonious 16 0.79 0.07 0.719 0.28 1.0
## professional 26 0.79 -0.15 0.468 0.53 1.1
## wellDesigned 31 0.76 0.06 0.645 0.36 1.0
## satisfying 28 0.61 0.29 0.716 0.28 1.4
## elegant 11 0.59 0.26 0.643 0.36 1.4
## appealing 1 0.57 0.40 0.813 0.19 1.8
## pleasing 24 0.56 0.38 0.773 0.23 1.8
## nice 22 0.55 0.41 0.795 0.21 1.9
## delightful 10 0.53 0.41 0.780 0.22 1.9
## likable 19 0.48 0.48 0.792 0.21 2.0
## colorHarmonious 8 0.41 0.27 0.407 0.59 1.7
## cluttered 7 0.28 -0.03 0.067 0.93 1.0
## creative 9 -0.19 0.89 0.584 0.42 1.1
## fascinating 15 -0.07 0.84 0.621 0.38 1.0
## provoking 27 -0.40 0.79 0.315 0.69 1.5
## artistic 2 -0.06 0.78 0.546 0.45 1.0
## interesting 17 0.08 0.71 0.602 0.40 1.0
## exciting 14 0.19 0.66 0.657 0.34 1.2
## engaging 12 0.28 0.59 0.662 0.34 1.4
## attractive 3 0.34 0.57 0.730 0.27 1.6
## beautiful 5 0.34 0.56 0.710 0.29 1.7
## tasteful 30 0.34 0.55 0.691 0.31 1.7
## motivating 21 0.29 0.54 0.597 0.40 1.5
## pretty 25 0.38 0.53 0.729 0.27 1.8
## enjoyable 13 0.42 0.53 0.790 0.21 1.9
## inviting 18 0.40 0.49 0.687 0.31 1.9
## sophisticated 29 0.28 0.48 0.506 0.49 1.6
## lovely 20 0.44 0.45 0.681 0.32 2.0
##
## PA1 PA2
## SS loadings 10.16 9.52
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.74
## PA2 0.74 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.90 0.813 0.19 1
## nice 22 0.89 0.795 0.20 1
## likable 19 0.89 0.794 0.21 1
## enjoyable 13 0.89 0.789 0.21 1
## delightful 10 0.88 0.781 0.22 1
## pleasing 24 0.88 0.771 0.23 1
## pretty 25 0.85 0.726 0.27 1
## attractive 3 0.85 0.722 0.28 1
## satisfying 28 0.84 0.705 0.29 1
## beautiful 5 0.84 0.703 0.30 1
## inviting 18 0.83 0.687 0.31 1
## tasteful 30 0.83 0.684 0.32 1
## lovely 20 0.83 0.682 0.32 1
## harmonious 16 0.81 0.652 0.35 1
## engaging 12 0.80 0.647 0.35 1
## elegant 11 0.80 0.633 0.37 1
## exciting 14 0.79 0.622 0.38 1
## motivating 21 0.77 0.588 0.41 1
## wellDesigned 31 0.76 0.582 0.42 1
## interesting 17 0.74 0.543 0.46 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.71 0.501 0.50 1
## sophisticated 29 0.71 0.500 0.50 1
## clean 6 0.67 0.449 0.55 1
## artistic 2 0.67 0.443 0.56 1
## organized 23 0.65 0.426 0.57 1
## creative 9 0.65 0.418 0.58 1
## colorHarmonious 8 0.64 0.406 0.59 1
## professional 26 0.60 0.355 0.64 1
## provoking 27 0.35 0.126 0.87 1
## cluttered 7 0.24 0.056 0.94 1
##
## PA1
## SS loadings 18.14
## Proportion Var 0.59
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 434 and the objective function was 6.31
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.83 0.10 0.691 0.31 1.0
## balanced 4 0.76 0.28 0.656 0.34 1.3
## harmonious 16 0.76 0.38 0.719 0.28 1.5
## clean 6 0.75 0.20 0.601 0.40 1.1
## wellDesigned 31 0.72 0.36 0.645 0.36 1.5
## appealing 1 0.68 0.59 0.813 0.19 2.0
## satisfying 28 0.68 0.51 0.716 0.28 1.9
## pleasing 24 0.67 0.57 0.773 0.23 2.0
## nice 22 0.67 0.59 0.795 0.21 2.0
## professional 26 0.66 0.18 0.468 0.53 1.1
## delightful 10 0.66 0.59 0.780 0.22 2.0
## elegant 11 0.64 0.48 0.643 0.36 1.8
## likable 19 0.63 0.63 0.792 0.21 2.0
## lovely 20 0.58 0.58 0.681 0.32 2.0
## colorHarmonious 8 0.49 0.41 0.407 0.59 1.9
## cluttered 7 0.24 0.09 0.067 0.93 1.3
## creative 9 0.19 0.74 0.584 0.42 1.1
## fascinating 15 0.28 0.74 0.621 0.38 1.3
## artistic 2 0.26 0.69 0.546 0.45 1.3
## interesting 17 0.37 0.68 0.602 0.40 1.5
## exciting 14 0.44 0.68 0.657 0.34 1.7
## attractive 3 0.54 0.66 0.730 0.27 1.9
## enjoyable 13 0.60 0.65 0.790 0.21 2.0
## engaging 12 0.49 0.65 0.662 0.34 1.9
## beautiful 5 0.54 0.65 0.710 0.29 1.9
## pretty 25 0.57 0.64 0.729 0.27 2.0
## tasteful 30 0.53 0.64 0.691 0.31 1.9
## inviting 18 0.56 0.61 0.687 0.31 2.0
## motivating 21 0.48 0.61 0.597 0.40 1.9
## provoking 27 -0.04 0.56 0.315 0.69 1.0
## sophisticated 29 0.45 0.55 0.506 0.49 1.9
##
## PA1 PA2
## SS loadings 10.11 9.57
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.79 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 1.06 -0.36 0.691 0.31 1.2
## clean 6 0.90 -0.18 0.601 0.40 1.1
## balanced 4 0.86 -0.07 0.656 0.34 1.0
## harmonious 16 0.79 0.07 0.719 0.28 1.0
## professional 26 0.79 -0.15 0.468 0.53 1.1
## wellDesigned 31 0.76 0.06 0.645 0.36 1.0
## satisfying 28 0.61 0.29 0.716 0.28 1.4
## elegant 11 0.59 0.26 0.643 0.36 1.4
## appealing 1 0.57 0.40 0.813 0.19 1.8
## pleasing 24 0.56 0.38 0.773 0.23 1.8
## nice 22 0.55 0.41 0.795 0.21 1.9
## delightful 10 0.53 0.41 0.780 0.22 1.9
## likable 19 0.48 0.48 0.792 0.21 2.0
## colorHarmonious 8 0.41 0.27 0.407 0.59 1.7
## cluttered 7 0.28 -0.03 0.067 0.93 1.0
## creative 9 -0.19 0.89 0.584 0.42 1.1
## fascinating 15 -0.07 0.84 0.621 0.38 1.0
## provoking 27 -0.40 0.79 0.315 0.69 1.5
## artistic 2 -0.06 0.78 0.546 0.45 1.0
## interesting 17 0.08 0.71 0.602 0.40 1.0
## exciting 14 0.19 0.66 0.657 0.34 1.2
## engaging 12 0.28 0.59 0.662 0.34 1.4
## attractive 3 0.34 0.57 0.730 0.27 1.6
## beautiful 5 0.34 0.56 0.710 0.29 1.7
## tasteful 30 0.34 0.55 0.691 0.31 1.7
## motivating 21 0.29 0.54 0.597 0.40 1.5
## pretty 25 0.38 0.53 0.729 0.27 1.8
## enjoyable 13 0.42 0.53 0.790 0.21 1.9
## inviting 18 0.40 0.49 0.687 0.31 1.9
## sophisticated 29 0.28 0.48 0.506 0.49 1.6
## lovely 20 0.44 0.45 0.681 0.32 2.0
##
## PA1 PA2
## SS loadings 10.16 9.52
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.74
## PA2 0.74 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.90 0.813 0.19 1
## nice 22 0.89 0.795 0.20 1
## likable 19 0.89 0.794 0.21 1
## enjoyable 13 0.89 0.789 0.21 1
## delightful 10 0.88 0.781 0.22 1
## pleasing 24 0.88 0.771 0.23 1
## pretty 25 0.85 0.726 0.27 1
## attractive 3 0.85 0.722 0.28 1
## satisfying 28 0.84 0.705 0.29 1
## beautiful 5 0.84 0.703 0.30 1
## inviting 18 0.83 0.687 0.31 1
## tasteful 30 0.83 0.684 0.32 1
## lovely 20 0.83 0.682 0.32 1
## harmonious 16 0.81 0.652 0.35 1
## engaging 12 0.80 0.647 0.35 1
## elegant 11 0.80 0.633 0.37 1
## exciting 14 0.79 0.622 0.38 1
## motivating 21 0.77 0.588 0.41 1
## wellDesigned 31 0.76 0.582 0.42 1
## interesting 17 0.74 0.543 0.46 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.71 0.501 0.50 1
## sophisticated 29 0.71 0.500 0.50 1
## clean 6 0.67 0.449 0.55 1
## artistic 2 0.67 0.443 0.56 1
## organized 23 0.65 0.426 0.57 1
## creative 9 0.65 0.418 0.58 1
## colorHarmonious 8 0.64 0.406 0.59 1
## professional 26 0.60 0.355 0.64 1
## provoking 27 0.35 0.126 0.87 1
## cluttered 7 0.24 0.056 0.94 1
##
## PA1
## SS loadings 18.14
## Proportion Var 0.59
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 434 and the objective function was 6.31
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.83 0.10 0.691 0.31 1.0
## balanced 4 0.76 0.28 0.656 0.34 1.3
## harmonious 16 0.76 0.38 0.719 0.28 1.5
## clean 6 0.75 0.20 0.601 0.40 1.1
## wellDesigned 31 0.72 0.36 0.645 0.36 1.5
## appealing 1 0.68 0.59 0.813 0.19 2.0
## satisfying 28 0.68 0.51 0.716 0.28 1.9
## pleasing 24 0.67 0.57 0.773 0.23 2.0
## nice 22 0.67 0.59 0.795 0.21 2.0
## professional 26 0.66 0.18 0.468 0.53 1.1
## delightful 10 0.66 0.59 0.780 0.22 2.0
## elegant 11 0.64 0.48 0.643 0.36 1.8
## likable 19 0.63 0.63 0.792 0.21 2.0
## lovely 20 0.58 0.58 0.681 0.32 2.0
## colorHarmonious 8 0.49 0.41 0.407 0.59 1.9
## cluttered 7 0.24 0.09 0.067 0.93 1.3
## creative 9 0.19 0.74 0.584 0.42 1.1
## fascinating 15 0.28 0.74 0.621 0.38 1.3
## artistic 2 0.26 0.69 0.546 0.45 1.3
## interesting 17 0.37 0.68 0.602 0.40 1.5
## exciting 14 0.44 0.68 0.657 0.34 1.7
## attractive 3 0.54 0.66 0.730 0.27 1.9
## enjoyable 13 0.60 0.65 0.790 0.21 2.0
## engaging 12 0.49 0.65 0.662 0.34 1.9
## beautiful 5 0.54 0.65 0.710 0.29 1.9
## pretty 25 0.57 0.64 0.729 0.27 2.0
## tasteful 30 0.53 0.64 0.691 0.31 1.9
## inviting 18 0.56 0.61 0.687 0.31 2.0
## motivating 21 0.48 0.61 0.597 0.40 1.9
## provoking 27 -0.04 0.56 0.315 0.69 1.0
## sophisticated 29 0.45 0.55 0.506 0.49 1.9
##
## PA1 PA2
## SS loadings 10.11 9.57
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.79 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 1.06 -0.36 0.691 0.31 1.2
## clean 6 0.90 -0.18 0.601 0.40 1.1
## balanced 4 0.86 -0.07 0.656 0.34 1.0
## harmonious 16 0.79 0.07 0.719 0.28 1.0
## professional 26 0.79 -0.15 0.468 0.53 1.1
## wellDesigned 31 0.76 0.06 0.645 0.36 1.0
## satisfying 28 0.61 0.29 0.716 0.28 1.4
## elegant 11 0.59 0.26 0.643 0.36 1.4
## appealing 1 0.57 0.40 0.813 0.19 1.8
## pleasing 24 0.56 0.38 0.773 0.23 1.8
## nice 22 0.55 0.41 0.795 0.21 1.9
## delightful 10 0.53 0.41 0.780 0.22 1.9
## likable 19 0.48 0.48 0.792 0.21 2.0
## colorHarmonious 8 0.41 0.27 0.407 0.59 1.7
## cluttered 7 0.28 -0.03 0.067 0.93 1.0
## creative 9 -0.19 0.89 0.584 0.42 1.1
## fascinating 15 -0.07 0.84 0.621 0.38 1.0
## provoking 27 -0.40 0.79 0.315 0.69 1.5
## artistic 2 -0.06 0.78 0.546 0.45 1.0
## interesting 17 0.08 0.71 0.602 0.40 1.0
## exciting 14 0.19 0.66 0.657 0.34 1.2
## engaging 12 0.28 0.59 0.662 0.34 1.4
## attractive 3 0.34 0.57 0.730 0.27 1.6
## beautiful 5 0.34 0.56 0.710 0.29 1.7
## tasteful 30 0.34 0.55 0.691 0.31 1.7
## motivating 21 0.29 0.54 0.597 0.40 1.5
## pretty 25 0.38 0.53 0.729 0.27 1.8
## enjoyable 13 0.42 0.53 0.790 0.21 1.9
## inviting 18 0.40 0.49 0.687 0.31 1.9
## sophisticated 29 0.28 0.48 0.506 0.49 1.6
## lovely 20 0.44 0.45 0.681 0.32 2.0
##
## PA1 PA2
## SS loadings 10.16 9.52
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.74
## PA2 0.74 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.90 0.813 0.19 1
## nice 22 0.89 0.795 0.20 1
## likable 19 0.89 0.794 0.21 1
## enjoyable 13 0.89 0.789 0.21 1
## delightful 10 0.88 0.781 0.22 1
## pleasing 24 0.88 0.771 0.23 1
## pretty 25 0.85 0.726 0.27 1
## attractive 3 0.85 0.722 0.28 1
## satisfying 28 0.84 0.705 0.29 1
## beautiful 5 0.84 0.703 0.30 1
## inviting 18 0.83 0.687 0.31 1
## tasteful 30 0.83 0.684 0.32 1
## lovely 20 0.83 0.682 0.32 1
## harmonious 16 0.81 0.652 0.35 1
## engaging 12 0.80 0.647 0.35 1
## elegant 11 0.80 0.633 0.37 1
## exciting 14 0.79 0.622 0.38 1
## motivating 21 0.77 0.588 0.41 1
## wellDesigned 31 0.76 0.582 0.42 1
## interesting 17 0.74 0.543 0.46 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.71 0.501 0.50 1
## sophisticated 29 0.71 0.500 0.50 1
## clean 6 0.67 0.449 0.55 1
## artistic 2 0.67 0.443 0.56 1
## organized 23 0.65 0.426 0.57 1
## creative 9 0.65 0.418 0.58 1
## colorHarmonious 8 0.64 0.406 0.59 1
## professional 26 0.60 0.355 0.64 1
## provoking 27 0.35 0.126 0.87 1
## cluttered 7 0.24 0.056 0.94 1
##
## PA1
## SS loadings 18.14
## Proportion Var 0.59
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 434 and the objective function was 6.31
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.83 0.10 0.691 0.31 1.0
## balanced 4 0.76 0.28 0.656 0.34 1.3
## harmonious 16 0.76 0.38 0.719 0.28 1.5
## clean 6 0.75 0.20 0.601 0.40 1.1
## wellDesigned 31 0.72 0.36 0.645 0.36 1.5
## appealing 1 0.68 0.59 0.813 0.19 2.0
## satisfying 28 0.68 0.51 0.716 0.28 1.9
## pleasing 24 0.67 0.57 0.773 0.23 2.0
## nice 22 0.67 0.59 0.795 0.21 2.0
## professional 26 0.66 0.18 0.468 0.53 1.1
## delightful 10 0.66 0.59 0.780 0.22 2.0
## elegant 11 0.64 0.48 0.643 0.36 1.8
## likable 19 0.63 0.63 0.792 0.21 2.0
## lovely 20 0.58 0.58 0.681 0.32 2.0
## colorHarmonious 8 0.49 0.41 0.407 0.59 1.9
## cluttered 7 0.24 0.09 0.067 0.93 1.3
## creative 9 0.19 0.74 0.584 0.42 1.1
## fascinating 15 0.28 0.74 0.621 0.38 1.3
## artistic 2 0.26 0.69 0.546 0.45 1.3
## interesting 17 0.37 0.68 0.602 0.40 1.5
## exciting 14 0.44 0.68 0.657 0.34 1.7
## attractive 3 0.54 0.66 0.730 0.27 1.9
## enjoyable 13 0.60 0.65 0.790 0.21 2.0
## engaging 12 0.49 0.65 0.662 0.34 1.9
## beautiful 5 0.54 0.65 0.710 0.29 1.9
## pretty 25 0.57 0.64 0.729 0.27 2.0
## tasteful 30 0.53 0.64 0.691 0.31 1.9
## inviting 18 0.56 0.61 0.687 0.31 2.0
## motivating 21 0.48 0.61 0.597 0.40 1.9
## provoking 27 -0.04 0.56 0.315 0.69 1.0
## sophisticated 29 0.45 0.55 0.506 0.49 1.9
##
## PA1 PA2
## SS loadings 10.11 9.57
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.79 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 1.06 -0.36 0.691 0.31 1.2
## clean 6 0.90 -0.18 0.601 0.40 1.1
## balanced 4 0.86 -0.07 0.656 0.34 1.0
## harmonious 16 0.79 0.07 0.719 0.28 1.0
## professional 26 0.79 -0.15 0.468 0.53 1.1
## wellDesigned 31 0.76 0.06 0.645 0.36 1.0
## satisfying 28 0.61 0.29 0.716 0.28 1.4
## elegant 11 0.59 0.26 0.643 0.36 1.4
## appealing 1 0.57 0.40 0.813 0.19 1.8
## pleasing 24 0.56 0.38 0.773 0.23 1.8
## nice 22 0.55 0.41 0.795 0.21 1.9
## delightful 10 0.53 0.41 0.780 0.22 1.9
## likable 19 0.48 0.48 0.792 0.21 2.0
## colorHarmonious 8 0.41 0.27 0.407 0.59 1.7
## cluttered 7 0.28 -0.03 0.067 0.93 1.0
## creative 9 -0.19 0.89 0.584 0.42 1.1
## fascinating 15 -0.07 0.84 0.621 0.38 1.0
## provoking 27 -0.40 0.79 0.315 0.69 1.5
## artistic 2 -0.06 0.78 0.546 0.45 1.0
## interesting 17 0.08 0.71 0.602 0.40 1.0
## exciting 14 0.19 0.66 0.657 0.34 1.2
## engaging 12 0.28 0.59 0.662 0.34 1.4
## attractive 3 0.34 0.57 0.730 0.27 1.6
## beautiful 5 0.34 0.56 0.710 0.29 1.7
## tasteful 30 0.34 0.55 0.691 0.31 1.7
## motivating 21 0.29 0.54 0.597 0.40 1.5
## pretty 25 0.38 0.53 0.729 0.27 1.8
## enjoyable 13 0.42 0.53 0.790 0.21 1.9
## inviting 18 0.40 0.49 0.687 0.31 1.9
## sophisticated 29 0.28 0.48 0.506 0.49 1.6
## lovely 20 0.44 0.45 0.681 0.32 2.0
##
## PA1 PA2
## SS loadings 10.16 9.52
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.74
## PA2 0.74 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
##
##
## ## Scree Plot and Parallel Analysis
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
##
##
##
##
## ## Exploratory Factor Analysis - 1 Factor - No Rotation
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## V PA1 h2 u2 com
## appealing 1 0.90 0.813 0.19 1
## nice 22 0.89 0.795 0.20 1
## likable 19 0.89 0.794 0.21 1
## enjoyable 13 0.89 0.789 0.21 1
## delightful 10 0.88 0.781 0.22 1
## pleasing 24 0.88 0.771 0.23 1
## pretty 25 0.85 0.726 0.27 1
## attractive 3 0.85 0.722 0.28 1
## satisfying 28 0.84 0.705 0.29 1
## beautiful 5 0.84 0.703 0.30 1
## inviting 18 0.83 0.687 0.31 1
## tasteful 30 0.83 0.684 0.32 1
## lovely 20 0.83 0.682 0.32 1
## harmonious 16 0.81 0.652 0.35 1
## engaging 12 0.80 0.647 0.35 1
## elegant 11 0.80 0.633 0.37 1
## exciting 14 0.79 0.622 0.38 1
## motivating 21 0.77 0.588 0.41 1
## wellDesigned 31 0.76 0.582 0.42 1
## interesting 17 0.74 0.543 0.46 1
## balanced 4 0.74 0.543 0.46 1
## fascinating 15 0.71 0.501 0.50 1
## sophisticated 29 0.71 0.500 0.50 1
## clean 6 0.67 0.449 0.55 1
## artistic 2 0.67 0.443 0.56 1
## organized 23 0.65 0.426 0.57 1
## creative 9 0.65 0.418 0.58 1
## colorHarmonious 8 0.64 0.406 0.59 1
## professional 26 0.60 0.355 0.64 1
## provoking 27 0.35 0.126 0.87 1
## cluttered 7 0.24 0.056 0.94 1
##
## PA1
## SS loadings 18.14
## Proportion Var 0.59
##
## Mean item complexity = 1
## Test of the hypothesis that 1 factor is sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 434 and the objective function was 6.31
##
## The root mean square of the residuals (RMSR) is 0.06
## The df corrected root mean square of the residuals is 0.06
##
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## PA1
## Correlation of (regression) scores with factors 0.99
## Multiple R square of scores with factors 0.98
## Minimum correlation of possible factor scores 0.96
##
##
## ## Exploratory Factor Analysis - 2 Factors - Varimax Rotation(Orthogonal rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 0.83 0.10 0.691 0.31 1.0
## balanced 4 0.76 0.28 0.656 0.34 1.3
## harmonious 16 0.76 0.38 0.719 0.28 1.5
## clean 6 0.75 0.20 0.601 0.40 1.1
## wellDesigned 31 0.72 0.36 0.645 0.36 1.5
## appealing 1 0.68 0.59 0.813 0.19 2.0
## satisfying 28 0.68 0.51 0.716 0.28 1.9
## pleasing 24 0.67 0.57 0.773 0.23 2.0
## nice 22 0.67 0.59 0.795 0.21 2.0
## professional 26 0.66 0.18 0.468 0.53 1.1
## delightful 10 0.66 0.59 0.780 0.22 2.0
## elegant 11 0.64 0.48 0.643 0.36 1.8
## likable 19 0.63 0.63 0.792 0.21 2.0
## lovely 20 0.58 0.58 0.681 0.32 2.0
## colorHarmonious 8 0.49 0.41 0.407 0.59 1.9
## cluttered 7 0.24 0.09 0.067 0.93 1.3
## creative 9 0.19 0.74 0.584 0.42 1.1
## fascinating 15 0.28 0.74 0.621 0.38 1.3
## artistic 2 0.26 0.69 0.546 0.45 1.3
## interesting 17 0.37 0.68 0.602 0.40 1.5
## exciting 14 0.44 0.68 0.657 0.34 1.7
## attractive 3 0.54 0.66 0.730 0.27 1.9
## enjoyable 13 0.60 0.65 0.790 0.21 2.0
## engaging 12 0.49 0.65 0.662 0.34 1.9
## beautiful 5 0.54 0.65 0.710 0.29 1.9
## pretty 25 0.57 0.64 0.729 0.27 2.0
## tasteful 30 0.53 0.64 0.691 0.31 1.9
## inviting 18 0.56 0.61 0.687 0.31 2.0
## motivating 21 0.48 0.61 0.597 0.40 1.9
## provoking 27 -0.04 0.56 0.315 0.69 1.0
## sophisticated 29 0.45 0.55 0.506 0.49 1.9
##
## PA1 PA2
## SS loadings 10.11 9.57
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.51 0.49
## Cumulative Proportion 0.51 1.00
##
## Mean item complexity = 1.7
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.95 0.94
## Multiple R square of scores with factors 0.90 0.89
## Minimum correlation of possible factor scores 0.79 0.77
##
##
## ## Exploratory Factor Analysis - 2 Factors - Promax Rotation(Pblique rotation)
## Factor Analysis using method = pa
## Call: fa(r = correlation(num, data), nfactors = factor, rotate = rotation,
## fm = "pa")
## Standardized loadings (pattern matrix) based upon correlation matrix
## item PA1 PA2 h2 u2 com
## organized 23 1.06 -0.36 0.691 0.31 1.2
## clean 6 0.90 -0.18 0.601 0.40 1.1
## balanced 4 0.86 -0.07 0.656 0.34 1.0
## harmonious 16 0.79 0.07 0.719 0.28 1.0
## professional 26 0.79 -0.15 0.468 0.53 1.1
## wellDesigned 31 0.76 0.06 0.645 0.36 1.0
## satisfying 28 0.61 0.29 0.716 0.28 1.4
## elegant 11 0.59 0.26 0.643 0.36 1.4
## appealing 1 0.57 0.40 0.813 0.19 1.8
## pleasing 24 0.56 0.38 0.773 0.23 1.8
## nice 22 0.55 0.41 0.795 0.21 1.9
## delightful 10 0.53 0.41 0.780 0.22 1.9
## likable 19 0.48 0.48 0.792 0.21 2.0
## colorHarmonious 8 0.41 0.27 0.407 0.59 1.7
## cluttered 7 0.28 -0.03 0.067 0.93 1.0
## creative 9 -0.19 0.89 0.584 0.42 1.1
## fascinating 15 -0.07 0.84 0.621 0.38 1.0
## provoking 27 -0.40 0.79 0.315 0.69 1.5
## artistic 2 -0.06 0.78 0.546 0.45 1.0
## interesting 17 0.08 0.71 0.602 0.40 1.0
## exciting 14 0.19 0.66 0.657 0.34 1.2
## engaging 12 0.28 0.59 0.662 0.34 1.4
## attractive 3 0.34 0.57 0.730 0.27 1.6
## beautiful 5 0.34 0.56 0.710 0.29 1.7
## tasteful 30 0.34 0.55 0.691 0.31 1.7
## motivating 21 0.29 0.54 0.597 0.40 1.5
## pretty 25 0.38 0.53 0.729 0.27 1.8
## enjoyable 13 0.42 0.53 0.790 0.21 1.9
## inviting 18 0.40 0.49 0.687 0.31 1.9
## sophisticated 29 0.28 0.48 0.506 0.49 1.6
## lovely 20 0.44 0.45 0.681 0.32 2.0
##
## PA1 PA2
## SS loadings 10.16 9.52
## Proportion Var 0.33 0.31
## Cumulative Var 0.33 0.63
## Proportion Explained 0.52 0.48
## Cumulative Proportion 0.52 1.00
##
## With factor correlations of
## PA1 PA2
## PA1 1.00 0.74
## PA2 0.74 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 2 factors are sufficient.
##
## The degrees of freedom for the null model are 465 and the objective function was 32.44
## The degrees of freedom for the model are 404 and the objective function was 4.67
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.04
##
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## PA1 PA2
## Correlation of (regression) scores with factors 0.98 0.98
## Multiple R square of scores with factors 0.96 0.96
## Minimum correlation of possible factor scores 0.93 0.91
colnames(df_nfactor) <- list_nfactor_column_name
df_nfactor[nrow(df_nfactor) + 1,] <- list_nfactor
row.names(df_nfactor) <- "Factors"
write.table(df_nfactor, paste("results/factor_numbers.tsv",sep=""),row.names=FALSE,sep='\t')
write.table(df,"results/factorLoadings_all_images.tsv",row.names=FALSE,sep='\t')
print(xtable(df),type="html")
| terms | PA1 Image 1 | PA1 Image 2 | PA1 Image 3 | PA1 Image 4 | PA1 Image 5 | PA1 Image 6 | PA1 Image 7 | PA1 Image 8 | PA1 Image 9 | PA1 Image 10 | PA1 Image 11 | PA1 Image 12 | PA1 Image 13 | PA1 Image 14 | PA1 Image 15 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | appealing | 0.85 | 0.80 | 0.80 | 0.84 | 0.87 | 0.83 | 0.88 | 0.85 | 0.85 | 0.88 | 0.85 | 0.88 | 0.88 | 0.83 | 0.90 |
| 2 | artistic | 0.52 | 0.49 | 0.51 | 0.59 | 0.66 | 0.63 | 0.69 | 0.61 | 0.56 | 0.66 | 0.64 | 0.69 | 0.55 | 0.58 | 0.67 |
| 3 | attractive | 0.84 | 0.78 | 0.81 | 0.81 | 0.86 | 0.87 | 0.89 | 0.84 | 0.84 | 0.86 | 0.85 | 0.87 | 0.86 | 0.84 | 0.85 |
| 4 | balanced | 0.69 | 0.63 | 0.61 | 0.73 | 0.71 | 0.69 | 0.59 | 0.70 | 0.65 | 0.77 | 0.74 | 0.66 | 0.68 | 0.71 | 0.74 |
| 5 | beautiful | 0.84 | 0.77 | 0.76 | 0.79 | 0.84 | 0.78 | 0.87 | 0.81 | 0.76 | 0.82 | 0.85 | 0.85 | 0.78 | 0.82 | 0.84 |
| 6 | clean | 0.73 | 0.70 | 0.71 | 0.64 | 0.70 | 0.60 | 0.66 | 0.70 | 0.60 | 0.68 | 0.71 | 0.71 | 0.63 | 0.73 | 0.67 |
| 7 | cluttered | 0.30 | -0.33 | 0.03 | 0.15 | 0.39 | 0.18 | 0.27 | 0.34 | 0.41 | 0.45 | 0.21 | -0.05 | 0.12 | 0.05 | 0.24 |
| 8 | colorHarmonious | 0.65 | 0.59 | 0.63 | 0.63 | 0.64 | 0.63 | 0.48 | 0.55 | 0.43 | 0.62 | 0.51 | 0.62 | 0.43 | 0.64 | 0.64 |
| 9 | creative | 0.53 | 0.49 | 0.55 | 0.60 | 0.67 | 0.62 | 0.66 | 0.70 | 0.62 | 0.68 | 0.65 | 0.64 | 0.58 | 0.54 | 0.65 |
| 10 | delightful | 0.86 | 0.74 | 0.78 | 0.85 | 0.83 | 0.81 | 0.89 | 0.82 | 0.79 | 0.82 | 0.86 | 0.88 | 0.89 | 0.84 | 0.88 |
| 11 | elegant | 0.83 | 0.76 | 0.71 | 0.78 | 0.74 | 0.68 | 0.83 | 0.69 | 0.71 | 0.84 | 0.76 | 0.80 | 0.78 | 0.74 | 0.80 |
| 12 | engaging | 0.79 | 0.70 | 0.76 | 0.74 | 0.78 | 0.78 | 0.82 | 0.83 | 0.74 | 0.76 | 0.79 | 0.77 | 0.80 | 0.73 | 0.80 |
| 13 | enjoyable | 0.87 | 0.78 | 0.83 | 0.86 | 0.86 | 0.84 | 0.88 | 0.87 | 0.84 | 0.87 | 0.85 | 0.88 | 0.83 | 0.85 | 0.89 |
| 14 | exciting | 0.79 | 0.66 | 0.72 | 0.76 | 0.81 | 0.76 | 0.81 | 0.77 | 0.70 | 0.77 | 0.82 | 0.77 | 0.79 | 0.75 | 0.79 |
| 15 | fascinating | 0.68 | 0.64 | 0.73 | 0.77 | 0.70 | 0.72 | 0.80 | 0.71 | 0.72 | 0.66 | 0.73 | 0.77 | 0.76 | 0.70 | 0.71 |
| 16 | harmonious | 0.79 | 0.69 | 0.76 | 0.75 | 0.82 | 0.74 | 0.74 | 0.74 | 0.69 | 0.80 | 0.77 | 0.80 | 0.76 | 0.75 | 0.81 |
| 17 | interesting | 0.70 | 0.70 | 0.71 | 0.74 | 0.76 | 0.71 | 0.73 | 0.74 | 0.61 | 0.64 | 0.70 | 0.73 | 0.74 | 0.59 | 0.74 |
| 18 | inviting | 0.83 | 0.74 | 0.71 | 0.73 | 0.82 | 0.80 | 0.84 | 0.85 | 0.78 | 0.78 | 0.83 | 0.78 | 0.84 | 0.76 | 0.83 |
| 19 | likable | 0.91 | 0.79 | 0.88 | 0.87 | 0.86 | 0.84 | 0.90 | 0.88 | 0.84 | 0.86 | 0.85 | 0.89 | 0.87 | 0.87 | 0.89 |
| 20 | lovely | 0.85 | 0.75 | 0.78 | 0.82 | 0.80 | 0.77 | 0.83 | 0.81 | 0.74 | 0.81 | 0.86 | 0.86 | 0.83 | 0.79 | 0.83 |
| 21 | motivating | 0.74 | 0.65 | 0.71 | 0.77 | 0.83 | 0.78 | 0.84 | 0.75 | 0.75 | 0.77 | 0.78 | 0.71 | 0.83 | 0.76 | 0.77 |
| 22 | nice | 0.90 | 0.81 | 0.81 | 0.82 | 0.87 | 0.83 | 0.87 | 0.87 | 0.81 | 0.85 | 0.84 | 0.82 | 0.89 | 0.82 | 0.89 |
| 23 | organized | 0.59 | 0.61 | 0.62 | 0.74 | 0.67 | 0.59 | 0.55 | 0.60 | 0.59 | 0.66 | 0.64 | 0.66 | 0.65 | 0.62 | 0.65 |
| 24 | pleasing | 0.85 | 0.80 | 0.84 | 0.88 | 0.89 | 0.87 | 0.90 | 0.84 | 0.80 | 0.88 | 0.87 | 0.88 | 0.87 | 0.84 | 0.88 |
| 25 | pretty | 0.85 | 0.76 | 0.77 | 0.78 | 0.81 | 0.81 | 0.88 | 0.79 | 0.76 | 0.80 | 0.84 | 0.85 | 0.83 | 0.86 | 0.85 |
| 26 | professional | 0.63 | 0.67 | 0.52 | 0.61 | 0.62 | 0.53 | 0.60 | 0.46 | 0.50 | 0.61 | 0.52 | 0.67 | 0.67 | 0.62 | 0.60 |
| 27 | provoking | 0.17 | 0.20 | 0.22 | 0.28 | 0.28 | 0.33 | 0.19 | 0.37 | 0.32 | 0.27 | 0.40 | 0.32 | 0.22 | 0.22 | 0.35 |
| 28 | satisfying | 0.77 | 0.73 | 0.77 | 0.83 | 0.85 | 0.80 | 0.90 | 0.80 | 0.82 | 0.85 | 0.86 | 0.87 | 0.85 | 0.81 | 0.84 |
| 29 | sophisticated | 0.68 | 0.63 | 0.62 | 0.63 | 0.61 | 0.62 | 0.73 | 0.65 | 0.66 | 0.63 | 0.63 | 0.75 | 0.71 | 0.71 | 0.71 |
| 30 | tasteful | 0.78 | 0.64 | 0.68 | 0.72 | 0.77 | 0.78 | 0.80 | 0.81 | 0.81 | 0.80 | 0.82 | 0.76 | 0.81 | 0.77 | 0.83 |
| 31 | wellDesigned | 0.76 | 0.71 | 0.67 | 0.77 | 0.81 | 0.73 | 0.69 | 0.71 | 0.73 | 0.74 | 0.76 | 0.81 | 0.81 | 0.66 | 0.76 |
remainingTerms <- df %>% filter_all(all_vars(. > 0.7))
write.table(remainingTerms,"results/factorLoadingsAbove_.7_all_images.tsv",row.names=FALSE,sep='\t')
print(xtable(remainingTerms),type="html")
| terms | PA1 Image 1 | PA1 Image 2 | PA1 Image 3 | PA1 Image 4 | PA1 Image 5 | PA1 Image 6 | PA1 Image 7 | PA1 Image 8 | PA1 Image 9 | PA1 Image 10 | PA1 Image 11 | PA1 Image 12 | PA1 Image 13 | PA1 Image 14 | PA1 Image 15 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | appealing | 0.85 | 0.80 | 0.80 | 0.84 | 0.87 | 0.83 | 0.88 | 0.85 | 0.85 | 0.88 | 0.85 | 0.88 | 0.88 | 0.83 | 0.90 |
| 2 | attractive | 0.84 | 0.78 | 0.81 | 0.81 | 0.86 | 0.87 | 0.89 | 0.84 | 0.84 | 0.86 | 0.85 | 0.87 | 0.86 | 0.84 | 0.85 |
| 3 | beautiful | 0.84 | 0.77 | 0.76 | 0.79 | 0.84 | 0.78 | 0.87 | 0.81 | 0.76 | 0.82 | 0.85 | 0.85 | 0.78 | 0.82 | 0.84 |
| 4 | delightful | 0.86 | 0.74 | 0.78 | 0.85 | 0.83 | 0.81 | 0.89 | 0.82 | 0.79 | 0.82 | 0.86 | 0.88 | 0.89 | 0.84 | 0.88 |
| 5 | enjoyable | 0.87 | 0.78 | 0.83 | 0.86 | 0.86 | 0.84 | 0.88 | 0.87 | 0.84 | 0.87 | 0.85 | 0.88 | 0.83 | 0.85 | 0.89 |
| 6 | inviting | 0.83 | 0.74 | 0.71 | 0.73 | 0.82 | 0.80 | 0.84 | 0.85 | 0.78 | 0.78 | 0.83 | 0.78 | 0.84 | 0.76 | 0.83 |
| 7 | likable | 0.91 | 0.79 | 0.88 | 0.87 | 0.86 | 0.84 | 0.90 | 0.88 | 0.84 | 0.86 | 0.85 | 0.89 | 0.87 | 0.87 | 0.89 |
| 8 | lovely | 0.85 | 0.75 | 0.78 | 0.82 | 0.80 | 0.77 | 0.83 | 0.81 | 0.74 | 0.81 | 0.86 | 0.86 | 0.83 | 0.79 | 0.83 |
| 9 | nice | 0.90 | 0.81 | 0.81 | 0.82 | 0.87 | 0.83 | 0.87 | 0.87 | 0.81 | 0.85 | 0.84 | 0.82 | 0.89 | 0.82 | 0.89 |
| 10 | pleasing | 0.85 | 0.80 | 0.84 | 0.88 | 0.89 | 0.87 | 0.90 | 0.84 | 0.80 | 0.88 | 0.87 | 0.88 | 0.87 | 0.84 | 0.88 |
| 11 | pretty | 0.85 | 0.76 | 0.77 | 0.78 | 0.81 | 0.81 | 0.88 | 0.79 | 0.76 | 0.80 | 0.84 | 0.85 | 0.83 | 0.86 | 0.85 |
| 12 | satisfying | 0.77 | 0.73 | 0.77 | 0.83 | 0.85 | 0.80 | 0.90 | 0.80 | 0.82 | 0.85 | 0.86 | 0.87 | 0.85 | 0.81 | 0.84 |
This code calculates the average ratings each image received from participants and saves them as plots with CIs. This analysis is partly exploratory as we check what would have happened if participants had used some of our reduced scale.
source("03_EFA/CI-Functions.R")
##
## Attaching package: 'boot'
## The following object is masked from 'package:psych':
##
## logit
participantResponseFiles <- list.files(path= "03_EFA/data",pattern = "\\.csv$") #names correspond to images, one participant per row, one word per
print(participantResponseFiles)
## [1] "vis01.csv" "vis02.csv" "vis03.csv" "vis04.csv" "vis05.csv" "vis06.csv"
## [7] "vis07.csv" "vis08.csv" "vis09.csv" "vis10.csv" "vis11.csv" "vis12.csv"
## [13] "vis13.csv" "vis14.csv" "vis15.csv"
This one cleans up the column names for each image’s responses
cleanColnames <- function(data){
newNames <- gsub("^.+?\\.(.+?)\\..*$", "\\1", colnames(data))
return(newNames)
}
This functions draws a bar chart with confidence intervals
barChart <- function(resultTable, techniques, nbTechs = -1, ymin, ymax, xAxisLabel = "I am the X axis", yAxisLabel = "I am the Y Label",plotTitle){
#tr <- t(resultTable)
if(nbTechs <= 0){
stop('Please give a positive number of Techniques, nbTechs');
}
tr <- as.data.frame(resultTable)
nbTechs <- nbTechs - 1 ; # seq will generate nb+1
#now need to calculate one number for the width of the interval
tr$CI2 <- tr$upperBound_CI - tr$mean
tr$CI1 <- tr$mean - tr$lowerBound_CI
#add a technique column
tr$technique <- factor(seq.int(0, nbTechs, 1));
breaks <- c(as.character(tr$technique));
print(tr)
g <- ggplot(tr, aes(x=technique, y=mean)) +
# geom_bar(stat="identity",fill = I("#CCCCCC")) +
geom_errorbar(aes(ymin=mean-CI1, ymax=mean+CI2),
width=0, # Width of the error bars
size = 1.1
) +
#labs(title="Overall time per technique") +
labs(x = xAxisLabel, y = yAxisLabel) +
scale_y_continuous(limits = c(ymin,ymax),breaks=1:7) +
scale_x_discrete(name="",breaks,techniques)+
coord_flip() +
ggtitle(plotTitle) +
theme(panel.background = element_rect(fill = 'white', colour = 'white'),axis.title=element_text(size = rel(1.2), colour = "black"),axis.text=element_text(size = rel(1.2), colour = "black"),panel.grid.major = element_line(colour = "#DDDDDD"),panel.grid.major.y = element_blank(), panel.grid.minor.y = element_blank())+
geom_point(size=2, colour="black") # dots
print(g)
}
This next function calculates the CIs of each image’s responses depending on the scale items (terms) given.
calculateDrawResponseCIs <- function(scaleItems){
imageCount <- length(participantResponseFiles)
pointEstimateVector = c()
lowerBoundVector = c()
upperBoundVector = c()
imageVector = c()
for (image in 1:imageCount){
data <- read.csv(paste("03_EFA/data/",participantResponseFiles[[image]],sep=""), encoding="UTF-8")
terms <- cleanColnames(data)
colnames(data) <- terms
#exploratory trying to see what would happen if we had had a lot fewer participants
#data <- data[sample(nrow(data), 24), ]
data <- data[scaleItems]
means <- rowMeans(data)
imageVector <- append(imageVector,image)
ci <- bootstrapMeanCI(means)
pointEstimateVector <- append(pointEstimateVector,ci[1])
upperBoundVector <- append(upperBoundVector,ci[3])
lowerBoundVector <- append(lowerBoundVector,ci[2])
}
df <- data.frame(image=imageVector,mean=pointEstimateVector,lowerBound_CI=lowerBoundVector,upperBound_CI=upperBoundVector)
plotTitle <- paste(paste("Average Rating for the",length(scaleItems)),"item scale")
barChart(df,df$image ,nbTechs = 15, ymin = 1, ymax = 7, "Image", "Average Ratings",plotTitle)
ggsave(paste("./results/",paste(plotTitle,".pdf",sep=""),sep=""), width=8, height=4, device=cairo_pdf)
print(df)
return(df)
}
As the ratings per image were done by different participant pools we don’t actually want to compare the ratings of each image.
generatePerImageTables <-function(dfs,titles){
imageCounts <- length(participantResponseFiles)
for(i in 1:imageCounts){
pointEstimateVector = c()
lowerBoundVector = c()
upperBoundVector = c()
scaleVector = c()
dflength <- length(dfs)
for(d in 1:dflength){
scaleVector <- append(scaleVector,titles[d])
df <- dfs[[d]]
pointEstimateVector <- append(pointEstimateVector,df$mean[df$image==i])
upperBoundVector <- append(upperBoundVector,df$upperBound_CI[df$image==i])
lowerBoundVector <- append(lowerBoundVector,df$lowerBound_CI[df$image==i])
}
df <- data.frame(scale=scaleVector,mean=pointEstimateVector,lowerBound_CI=lowerBoundVector,upperBound_CI=upperBoundVector)
plotTitle <- paste(paste("Image",i)," Ratings Per Scale")
barChart(df,df$scale ,nbTechs = dflength, ymin = 1, ymax = 7, "Image", "Average Ratings",plotTitle)
path<-paste("./results/",paste(plotTitle,".pdf",sep=""),sep="")
print(path)
ggsave(path, width=8, height=4,device=cairo_pdf)
}
}
And now we run our tests
data <- read.csv(paste("03_EFA/data/",participantResponseFiles[[1]],sep=""), encoding="UTF-8")
scaleItems <- cleanColnames(data)
df31 <- calculateDrawResponseCIs(scaleItems)
## image mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 1 3.974755 3.796985 4.153331 0.1785762 0.1777700 0
## 2 2 4.920186 4.796959 5.033283 0.1130972 0.1232275 1
## 3 3 4.977655 4.829053 5.104957 0.1273013 0.1486024 2
## 4 4 4.640505 4.477054 4.794313 0.1538078 0.1634519 3
## 5 5 3.598448 3.432593 3.765694 0.1672456 0.1658551 4
## 6 6 4.359130 4.216120 4.508112 0.1489823 0.1430101 5
## 7 7 3.611879 3.429459 3.799131 0.1872515 0.1824202 6
## 8 8 3.338125 3.166305 3.504257 0.1661321 0.1718202 7
## 9 9 2.784523 2.637046 2.949720 0.1651967 0.1474777 8
## 10 10 3.292157 3.118713 3.459972 0.1678152 0.1734440 9
## 11 11 3.950283 3.778517 4.117025 0.1667422 0.1717659 10
## 12 12 4.329414 4.162565 4.492664 0.1632502 0.1668484 11
## 13 13 4.141023 3.968008 4.310758 0.1697348 0.1730153 12
## 14 14 3.850057 3.683969 4.008753 0.1586967 0.1660880 13
## 15 15 3.913176 3.734968 4.088589 0.1754133 0.1782079 14
## image mean lowerBound_CI upperBound_CI
## 1 1 3.974755 3.796985 4.153331
## 2 2 4.920186 4.796959 5.033283
## 3 3 4.977655 4.829053 5.104957
## 4 4 4.640505 4.477054 4.794313
## 5 5 3.598448 3.432593 3.765694
## 6 6 4.359130 4.216120 4.508112
## 7 7 3.611879 3.429459 3.799131
## 8 8 3.338125 3.166305 3.504257
## 9 9 2.784523 2.637046 2.949720
## 10 10 3.292157 3.118713 3.459972
## 11 11 3.950283 3.778517 4.117025
## 12 12 4.329414 4.162565 4.492664
## 13 13 4.141023 3.968008 4.310758
## 14 14 3.850057 3.683969 4.008753
## 15 15 3.913176 3.734968 4.088589
scaleItems = c("enjoyable","likable","pleasing")
df3 <- calculateDrawResponseCIs(scaleItems)
## image mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 1 3.951087 3.715580 4.181159 0.2300725 0.2355072 0
## 2 2 5.249141 5.094502 5.388316 0.1391753 0.1546392 1
## 3 3 5.243902 5.047154 5.404878 0.1609756 0.1967480 2
## 4 4 4.731959 4.524308 4.927835 0.1958763 0.2076504 3
## 5 5 3.597484 3.394654 3.798742 0.2012579 0.2028302 4
## 6 6 4.579511 4.394495 4.755352 0.1758410 0.1850153 5
## 7 7 3.474427 3.239859 3.717813 0.2433862 0.2345679 6
## 8 8 3.492228 3.269430 3.708026 0.2157977 0.2227979 7
## 9 9 2.500000 2.323037 2.696629 0.1966292 0.1769628 8
## 10 10 3.159558 2.947867 3.370284 0.2107262 0.2116904 9
## 11 11 4.013746 3.805842 4.216495 0.2027491 0.2079038 10
## 12 12 4.495895 4.285714 4.697199 0.2013046 0.2101806 11
## 13 13 4.228621 4.012216 4.432810 0.2041885 0.2164049 12
## 14 14 3.480737 3.262982 3.686767 0.2060302 0.2177554 13
## 15 15 3.925373 3.703151 4.137645 0.2122720 0.2222222 14
## image mean lowerBound_CI upperBound_CI
## 1 1 3.951087 3.715580 4.181159
## 2 2 5.249141 5.094502 5.388316
## 3 3 5.243902 5.047154 5.404878
## 4 4 4.731959 4.524308 4.927835
## 5 5 3.597484 3.394654 3.798742
## 6 6 4.579511 4.394495 4.755352
## 7 7 3.474427 3.239859 3.717813
## 8 8 3.492228 3.269430 3.708026
## 9 9 2.500000 2.323037 2.696629
## 10 10 3.159558 2.947867 3.370284
## 11 11 4.013746 3.805842 4.216495
## 12 12 4.495895 4.285714 4.697199
## 13 13 4.228621 4.012216 4.432810
## 14 14 3.480737 3.262982 3.686767
## 15 15 3.925373 3.703151 4.137645
scaleItems = c("enjoyable","likable","pleasing","nice")
df4 <- calculateDrawResponseCIs(scaleItems)
## image mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 1 3.970109 3.737772 4.199728 0.2296196 0.2323370 0
## 2 2 5.302835 5.150773 5.436856 0.1340206 0.1520619 1
## 3 3 5.237805 5.051220 5.393902 0.1560976 0.1865854 2
## 4 4 4.731959 4.530928 4.923969 0.1920103 0.2010309 3
## 5 5 3.666274 3.465802 3.866745 0.2004717 0.2004717 4
## 6 6 4.592890 4.411697 4.770642 0.1777523 0.1811927 5
## 7 7 3.513228 3.281746 3.748677 0.2354497 0.2314815 6
## 8 8 3.531088 3.309585 3.746114 0.2150259 0.2215026 7
## 9 9 2.546348 2.375000 2.744382 0.1980337 0.1713483 8
## 10 10 3.163507 2.958531 3.366114 0.2026066 0.2049763 9
## 11 11 4.052835 3.843148 4.247423 0.1945876 0.2096872 10
## 12 12 4.538177 4.334975 4.735222 0.1970443 0.2032020 11
## 13 13 4.243455 4.031414 4.446335 0.2028796 0.2120419 12
## 14 14 3.545226 3.327889 3.747487 0.2022613 0.2173367 13
## 15 15 3.947761 3.730100 4.161692 0.2139303 0.2176617 14
## image mean lowerBound_CI upperBound_CI
## 1 1 3.970109 3.737772 4.199728
## 2 2 5.302835 5.150773 5.436856
## 3 3 5.237805 5.051220 5.393902
## 4 4 4.731959 4.530928 4.923969
## 5 5 3.666274 3.465802 3.866745
## 6 6 4.592890 4.411697 4.770642
## 7 7 3.513228 3.281746 3.748677
## 8 8 3.531088 3.309585 3.746114
## 9 9 2.546348 2.375000 2.744382
## 10 10 3.163507 2.958531 3.366114
## 11 11 4.052835 3.843148 4.247423
## 12 12 4.538177 4.334975 4.735222
## 13 13 4.243455 4.031414 4.446335
## 14 14 3.545226 3.327889 3.747487
## 15 15 3.947761 3.730100 4.161692
scaleItems = c("enjoyable","likable","pleasing","nice","appealing")
df5 <- calculateDrawResponseCIs(scaleItems)
## image mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 1 3.978261 3.746739 4.205435 0.2271739 0.2315217 0
## 2 2 5.296907 5.145361 5.431959 0.1350515 0.1515464 1
## 3 3 5.234146 5.055272 5.390851 0.1567048 0.1788743 2
## 4 4 4.746392 4.547423 4.938144 0.1917526 0.1989691 3
## 5 5 3.669811 3.471698 3.866981 0.1971698 0.1981132 4
## 6 6 4.590826 4.411510 4.766055 0.1752294 0.1793159 5
## 7 7 3.488889 3.260317 3.729101 0.2402116 0.2285714 6
## 8 8 3.504663 3.289119 3.719171 0.2145078 0.2155440 7
## 9 9 2.574157 2.401124 2.775469 0.2013117 0.1730337 8
## 10 10 3.194313 2.988626 3.395261 0.2009479 0.2056872 9
## 11 11 4.018557 3.809775 4.215464 0.1969072 0.2087821 10
## 12 12 4.527094 4.321182 4.721182 0.1940887 0.2059113 11
## 13 13 4.229319 4.015707 4.431414 0.2020942 0.2136126 12
## 14 14 3.539698 3.323618 3.744724 0.2050251 0.2160804 13
## 15 15 3.943284 3.726725 4.158209 0.2149254 0.2165589 14
## image mean lowerBound_CI upperBound_CI
## 1 1 3.978261 3.746739 4.205435
## 2 2 5.296907 5.145361 5.431959
## 3 3 5.234146 5.055272 5.390851
## 4 4 4.746392 4.547423 4.938144
## 5 5 3.669811 3.471698 3.866981
## 6 6 4.590826 4.411510 4.766055
## 7 7 3.488889 3.260317 3.729101
## 8 8 3.504663 3.289119 3.719171
## 9 9 2.574157 2.401124 2.775469
## 10 10 3.194313 2.988626 3.395261
## 11 11 4.018557 3.809775 4.215464
## 12 12 4.527094 4.321182 4.721182
## 13 13 4.229319 4.015707 4.431414
## 14 14 3.539698 3.323618 3.744724
## 15 15 3.943284 3.726725 4.158209
dfs <- list(df3,df4,df5,df31)
generatePerImageTables(list(df3,df4,df5,df31),c("3-Item","4-Item","5-Item","31-Item"))
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 3.951087 3.715580 4.181159 0.2300725 0.2355072 0
## 2 4-Item 3.970109 3.737772 4.199728 0.2296196 0.2323370 1
## 3 5-Item 3.978261 3.746739 4.205435 0.2271739 0.2315217 2
## 4 31-Item 3.974755 3.796985 4.153331 0.1785762 0.1777700 3
## [1] "./results/Image 1 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 5.249141 5.094502 5.388316 0.1391753 0.1546392 0
## 2 4-Item 5.302835 5.150773 5.436856 0.1340206 0.1520619 1
## 3 5-Item 5.296907 5.145361 5.431959 0.1350515 0.1515464 2
## 4 31-Item 4.920186 4.796959 5.033283 0.1130972 0.1232275 3
## [1] "./results/Image 2 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 5.243902 5.047154 5.404878 0.1609756 0.1967480 0
## 2 4-Item 5.237805 5.051220 5.393902 0.1560976 0.1865854 1
## 3 5-Item 5.234146 5.055272 5.390851 0.1567048 0.1788743 2
## 4 31-Item 4.977655 4.829053 5.104957 0.1273013 0.1486024 3
## [1] "./results/Image 3 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 4.731959 4.524308 4.927835 0.1958763 0.2076504 0
## 2 4-Item 4.731959 4.530928 4.923969 0.1920103 0.2010309 1
## 3 5-Item 4.746392 4.547423 4.938144 0.1917526 0.1989691 2
## 4 31-Item 4.640505 4.477054 4.794313 0.1538078 0.1634519 3
## [1] "./results/Image 4 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 3.597484 3.394654 3.798742 0.2012579 0.2028302 0
## 2 4-Item 3.666274 3.465802 3.866745 0.2004717 0.2004717 1
## 3 5-Item 3.669811 3.471698 3.866981 0.1971698 0.1981132 2
## 4 31-Item 3.598448 3.432593 3.765694 0.1672456 0.1658551 3
## [1] "./results/Image 5 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 4.579511 4.394495 4.755352 0.1758410 0.1850153 0
## 2 4-Item 4.592890 4.411697 4.770642 0.1777523 0.1811927 1
## 3 5-Item 4.590826 4.411510 4.766055 0.1752294 0.1793159 2
## 4 31-Item 4.359130 4.216120 4.508112 0.1489823 0.1430101 3
## [1] "./results/Image 6 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 3.474427 3.239859 3.717813 0.2433862 0.2345679 0
## 2 4-Item 3.513228 3.281746 3.748677 0.2354497 0.2314815 1
## 3 5-Item 3.488889 3.260317 3.729101 0.2402116 0.2285714 2
## 4 31-Item 3.611879 3.429459 3.799131 0.1872515 0.1824202 3
## [1] "./results/Image 7 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 3.492228 3.269430 3.708026 0.2157977 0.2227979 0
## 2 4-Item 3.531088 3.309585 3.746114 0.2150259 0.2215026 1
## 3 5-Item 3.504663 3.289119 3.719171 0.2145078 0.2155440 2
## 4 31-Item 3.338125 3.166305 3.504257 0.1661321 0.1718202 3
## [1] "./results/Image 8 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 2.500000 2.323037 2.696629 0.1966292 0.1769628 0
## 2 4-Item 2.546348 2.375000 2.744382 0.1980337 0.1713483 1
## 3 5-Item 2.574157 2.401124 2.775469 0.2013117 0.1730337 2
## 4 31-Item 2.784523 2.637046 2.949720 0.1651967 0.1474777 3
## [1] "./results/Image 9 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 3.159558 2.947867 3.370284 0.2107262 0.2116904 0
## 2 4-Item 3.163507 2.958531 3.366114 0.2026066 0.2049763 1
## 3 5-Item 3.194313 2.988626 3.395261 0.2009479 0.2056872 2
## 4 31-Item 3.292157 3.118713 3.459972 0.1678152 0.1734440 3
## [1] "./results/Image 10 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 4.013746 3.805842 4.216495 0.2027491 0.2079038 0
## 2 4-Item 4.052835 3.843148 4.247423 0.1945876 0.2096872 1
## 3 5-Item 4.018557 3.809775 4.215464 0.1969072 0.2087821 2
## 4 31-Item 3.950283 3.778517 4.117025 0.1667422 0.1717659 3
## [1] "./results/Image 11 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 4.495895 4.285714 4.697199 0.2013046 0.2101806 0
## 2 4-Item 4.538177 4.334975 4.735222 0.1970443 0.2032020 1
## 3 5-Item 4.527094 4.321182 4.721182 0.1940887 0.2059113 2
## 4 31-Item 4.329414 4.162565 4.492664 0.1632502 0.1668484 3
## [1] "./results/Image 12 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 4.228621 4.012216 4.432810 0.2041885 0.2164049 0
## 2 4-Item 4.243455 4.031414 4.446335 0.2028796 0.2120419 1
## 3 5-Item 4.229319 4.015707 4.431414 0.2020942 0.2136126 2
## 4 31-Item 4.141023 3.968008 4.310758 0.1697348 0.1730153 3
## [1] "./results/Image 13 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 3.480737 3.262982 3.686767 0.2060302 0.2177554 0
## 2 4-Item 3.545226 3.327889 3.747487 0.2022613 0.2173367 1
## 3 5-Item 3.539698 3.323618 3.744724 0.2050251 0.2160804 2
## 4 31-Item 3.850057 3.683969 4.008753 0.1586967 0.1660880 3
## [1] "./results/Image 14 Ratings Per Scale.pdf"
## scale mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 3-Item 3.925373 3.703151 4.137645 0.2122720 0.2222222 0
## 2 4-Item 3.947761 3.730100 4.161692 0.2139303 0.2176617 1
## 3 5-Item 3.943284 3.726725 4.158209 0.2149254 0.2165589 2
## 4 31-Item 3.913176 3.734968 4.088589 0.1754133 0.1782079 3
## [1] "./results/Image 15 Ratings Per Scale.pdf"
# import library
library(lavaan) #CFA
## This is lavaan 0.6-12
## lavaan is FREE software! Please report any bugs.
##
## Attaching package: 'lavaan'
## The following object is masked from 'package:psych':
##
## cor2cov
library(ltm) # Cronbach's alpha
## Loading required package: MASS
##
## Attaching package: 'MASS'
## The following object is masked from 'package:dplyr':
##
## select
## Loading required package: msm
##
## Attaching package: 'msm'
## The following object is masked from 'package:boot':
##
## cav
## Loading required package: polycor
##
## Attaching package: 'polycor'
## The following object is masked from 'package:psych':
##
## polyserial
##
## Attaching package: 'ltm'
## The following object is masked from 'package:psych':
##
## factor.scores
# import data
data <- read.csv("04_CFA/validation results + demographics - valid - PID removed.csv" , encoding="UTF-8")
data
## id submitdate lastpage startlanguage seed
## 1 8 2022-03-26 23:56:31 7 en 351477190
## 2 9 2022-03-26 23:57:24 7 en 1410639181
## 3 10 2022-03-26 23:57:23 7 en 2031954271
## 4 11 2022-03-26 23:57:37 7 en 989660323
## 5 12 2022-03-26 23:57:33 7 en 1064436556
## 6 13 2022-03-26 23:59:52 7 en 1223970187
## 7 14 2022-03-27 00:01:01 7 en 713772528
## 8 15 2022-03-26 23:59:17 7 en 1971082747
## 9 18 2022-03-27 00:01:58 7 en 490221524
## 10 19 2022-03-27 00:02:19 7 en 1527133111
## 11 20 2022-03-27 00:04:37 7 en 834559536
## 12 21 2022-03-27 00:03:24 7 en 847752055
## 13 22 2022-03-27 00:01:05 7 en 26174271
## 14 23 2022-03-27 00:03:45 7 en 1283381430
## 15 24 2022-03-27 00:02:49 7 en 1721400207
## 16 25 2022-03-27 00:01:59 7 en 239810451
## 17 26 2022-03-27 00:02:42 7 en 270646464
## 18 27 2022-03-27 00:02:30 7 en 212207794
## 19 28 2022-03-27 00:02:52 7 en 626853214
## 20 29 2022-03-27 00:06:20 7 en 668469237
## 21 30 2022-03-27 00:03:43 7 en 224276825
## 22 31 2022-03-27 00:02:40 7 en 280008692
## 23 32 2022-03-27 00:02:25 7 en 1727944818
## 24 34 2022-03-27 00:03:30 7 en 1744605935
## 25 35 2022-03-27 00:02:35 7 en 1450041428
## 26 36 2022-03-27 00:02:49 7 en 1175021831
## 27 37 2022-03-27 00:03:16 7 en 1517785190
## 28 38 2022-03-27 00:06:24 7 en 1478589615
## 29 39 2022-03-27 00:03:20 7 en 402771416
## 30 40 2022-03-27 00:04:33 7 en 662759214
## 31 41 2022-03-27 00:02:19 7 en 2131180490
## 32 42 2022-03-27 00:05:25 7 en 160474725
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## 34 44 2022-03-27 00:06:14 7 en 611399631
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## 36 46 2022-03-27 00:04:09 7 en 2047119844
## 37 47 2022-03-27 00:04:14 7 en 1416741333
## 38 48 2022-03-27 00:02:23 7 en 1369295729
## 39 49 2022-03-27 00:01:39 7 en 1560648152
## 40 50 2022-03-27 00:02:30 7 en 2024569501
## 41 51 2022-03-27 00:06:37 7 en 869320385
## 42 53 2022-03-27 00:02:22 7 en 1806290188
## 43 55 2022-03-27 00:03:28 7 en 373274611
## 44 56 2022-03-27 00:06:00 7 en 949994066
## 45 57 2022-03-27 00:19:16 7 en 1840933426
## 46 59 2022-03-27 00:11:57 7 en 1996200907
## 47 60 2022-03-27 00:11:41 7 en 1392013983
## 48 61 2022-03-27 00:16:18 7 en 1450907733
## 49 62 2022-03-27 00:11:44 7 en 466099979
## 50 63 2022-03-27 00:13:52 7 en 1116238585
## 51 64 2022-03-27 00:12:16 7 en 1715950145
## 52 65 2022-03-27 00:13:49 7 en 969544991
## 53 66 2022-03-27 00:12:28 7 en 1885442046
## 54 67 2022-03-27 00:12:48 7 en 184903426
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## 62 76 2022-03-27 00:14:03 7 en 214420002
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## 64 79 2022-03-27 00:14:39 7 en 1690448874
## 65 80 2022-03-27 00:13:18 7 en 445394249
## 66 81 2022-03-27 00:19:08 7 en 152220755
## 67 82 2022-03-27 00:13:26 7 en 1397989153
## 68 83 2022-03-27 00:15:51 7 en 1573341895
## 69 84 2022-03-27 00:17:24 7 en 1107769839
## 70 85 2022-03-27 00:15:03 7 en 991747801
## 71 86 2022-03-27 00:16:17 7 en 1605025129
## 72 87 2022-03-27 00:14:21 7 en 808580792
## 73 88 2022-03-27 00:17:22 7 en 537666697
## 74 89 2022-03-27 00:14:44 7 en 809320047
## 75 90 2022-03-27 00:18:04 7 en 1149330773
## 76 91 2022-03-27 00:15:05 7 en 1712104494
## 77 92 2022-03-27 00:17:41 7 en 583361058
## 78 93 2022-03-27 00:15:43 7 en 1155910031
## 79 94 2022-03-27 00:16:06 7 en 1654736475
## 80 95 2022-03-27 00:18:20 7 en 1966771664
## 81 96 2022-03-27 00:15:28 7 en 1343567915
## 82 97 2022-03-27 00:17:02 7 en 1312709902
## 83 98 2022-03-27 00:18:43 7 en 2130356613
## 84 99 2022-03-27 00:16:21 7 en 2053540664
## 85 100 2022-03-27 00:15:44 7 en 305615445
## 86 101 2022-03-27 00:16:21 7 en 1902083851
## 87 102 2022-03-27 00:16:12 7 en 256204230
## 88 103 2022-03-27 00:16:27 7 en 1848658893
## 89 104 2022-03-27 00:16:58 7 en 1831202090
## 90 106 2022-03-27 00:16:19 7 en 902964213
## 91 108 2022-03-27 00:24:04 7 en 940687832
## 92 109 2022-03-27 00:31:06 7 en 1159833479
## 93 110 2022-03-27 00:21:09 7 en 124741960
## 94 111 2022-03-27 00:23:49 7 en 1470406330
## 95 114 2022-03-27 00:28:09 7 en 1172580729
## 96 115 2022-03-27 00:26:53 7 en 1938839597
## 97 116 2022-03-27 00:31:42 7 en 1506644463
## 98 117 2022-03-27 00:30:29 7 en 2032810759
## 99 118 2022-03-27 00:31:34 7 en 1975180656
## 100 119 2022-03-27 00:30:33 7 en 1638074741
## 101 120 2022-03-27 00:31:11 7 en 1708250164
## 102 121 2022-03-27 00:34:55 7 en 136670214
## 103 123 2022-03-27 00:30:57 7 en 744606833
## 104 124 2022-03-27 00:32:07 7 en 346692507
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## 106 126 2022-03-27 00:31:51 7 en 1952474206
## 107 127 2022-03-27 00:31:24 7 en 777032880
## 108 128 2022-03-27 00:33:20 7 en 416340410
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## 110 130 2022-03-27 00:30:18 7 en 1529604254
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## 112 132 2022-03-27 00:30:44 7 en 150188812
## 113 133 2022-03-27 00:30:30 7 en 1153376935
## 114 134 2022-03-27 00:34:08 7 en 1246444638
## 115 135 2022-03-27 00:30:46 7 en 2077452298
## 116 136 2022-03-27 00:30:11 7 en 1935548030
## 117 138 2022-03-27 00:31:59 7 en 1404951514
## 118 139 2022-03-27 00:31:57 7 en 1776382019
## 119 140 2022-03-27 00:31:39 7 en 1815640035
## 120 141 2022-03-27 00:30:55 7 en 1275630878
## 121 142 2022-03-27 00:31:04 7 en 1337025848
## 122 143 2022-03-27 00:30:52 7 en 666785783
## 123 144 2022-03-27 00:34:37 7 en 1904896797
## 124 145 2022-03-27 00:29:54 7 en 195632457
## 125 146 2022-03-27 00:31:41 7 en 83645806
## 126 147 2022-03-27 00:31:07 7 en 1389269412
## 127 148 2022-03-27 00:31:32 7 en 1482388818
## 128 149 2022-03-27 00:38:35 7 en 643843702
## 129 150 2022-03-27 00:31:58 7 en 216688808
## 130 151 2022-03-27 00:32:34 7 en 914305883
## 131 152 2022-03-27 00:31:09 7 en 266540852
## 132 153 2022-03-27 00:38:24 7 en 1144500704
## 133 154 2022-03-27 00:32:18 7 en 277345730
## 134 155 2022-03-27 00:32:33 7 en 968509642
## 135 156 2022-03-27 00:33:03 7 en 716216283
## 136 157 2022-03-27 00:33:29 7 en 1657733315
## 137 159 2022-03-27 00:41:40 7 en 706072613
## 138 160 2022-03-27 00:44:19 7 en 2064149465
## 139 162 2022-03-27 00:42:18 7 en 686114565
## 140 163 2022-03-27 00:42:31 7 en 1888763582
## 141 165 2022-03-27 00:43:55 7 en 1560135231
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## 145 169 2022-03-27 00:42:11 7 en 1289839941
## 146 170 2022-03-27 00:42:08 7 en 1181613449
## 147 171 2022-03-27 00:46:50 7 en 590041381
## 148 172 2022-03-27 00:41:45 7 en 1298679423
## 149 173 2022-03-27 00:42:13 7 en 1387770136
## 150 174 2022-03-27 00:42:21 7 en 550358639
## 151 175 2022-03-27 00:42:25 7 en 2009496350
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## 153 178 2022-03-27 00:45:31 7 en 1553650487
## 154 179 2022-03-27 00:42:47 7 en 421156216
## 155 181 2022-03-27 00:42:23 7 en 971579170
## 156 182 2022-03-27 00:41:43 7 en 1338747058
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## 163 189 2022-03-27 00:47:07 7 en 618541009
## 164 190 2022-03-27 00:43:01 7 en 1609562035
## 165 191 2022-03-27 00:41:48 7 en 1624843907
## 166 192 2022-03-27 00:48:34 7 en 852523172
## 167 193 2022-03-27 00:47:47 7 en 997043444
## 168 194 2022-03-27 00:44:22 7 en 2067726058
## 169 195 2022-03-27 00:45:03 7 en 421621003
## 170 196 2022-03-27 00:47:12 7 en 212194673
## 171 197 2022-03-27 00:43:05 7 en 258353911
## 172 198 2022-03-27 00:44:17 7 en 922529271
## 173 199 2022-03-27 00:52:32 7 en 91705517
## 174 200 2022-03-27 00:45:32 7 en 1414722674
## 175 201 2022-03-27 00:45:43 7 en 1361757621
## 176 203 2022-03-27 00:52:46 7 en 1561905781
## 177 204 2022-03-27 01:10:30 7 en 1916111024
## 178 205 2022-03-27 00:59:38 7 en 1396922884
## 179 206 2022-03-27 00:58:47 7 en 5262107
## 180 207 2022-03-27 01:00:14 7 en 1936015519
## 181 208 2022-03-27 01:07:08 7 en 1392587835
## 182 209 2022-03-27 01:01:22 7 en 1462662073
## 183 210 2022-03-27 01:02:44 7 en 1461400667
## 184 211 2022-03-27 01:02:01 7 en 1534726189
## 185 212 2022-03-27 01:02:18 7 en 1050306609
## 186 213 2022-03-27 00:59:27 7 en 1558541422
## 187 214 2022-03-27 01:00:17 7 en 180458183
## 188 215 2022-03-27 00:59:25 7 en 1047531303
## 189 216 2022-03-27 00:58:49 7 en 2080707274
## 190 217 2022-03-27 00:59:16 7 en 1652528165
## 191 218 2022-03-27 00:59:37 7 en 423632619
## 192 219 2022-03-27 00:59:56 7 en 2083770783
## 193 220 2022-03-27 01:00:56 7 en 978357814
## 194 221 2022-03-27 01:03:16 7 en 1366682049
## 195 222 2022-03-27 01:02:46 7 en 1564880048
## 196 223 2022-03-27 01:03:17 7 en 674964480
## 197 224 2022-03-27 01:11:38 7 en 1602419886
## startdate datestamp CF001 CF002 education
## 1 2022-03-26 23:54:44 2022-03-26 23:56:31 Y Y A1
## 2 2022-03-26 23:54:56 2022-03-26 23:57:24 Y Y A1
## 3 2022-03-26 23:55:11 2022-03-26 23:57:23 Y Y A1
## 4 2022-03-26 23:55:16 2022-03-26 23:57:37 Y Y A1
## 5 2022-03-26 23:55:26 2022-03-26 23:57:33 Y Y -oth-
## 6 2022-03-26 23:55:27 2022-03-26 23:59:52 Y Y A1
## 7 2022-03-26 23:55:34 2022-03-27 00:01:01 Y Y A1
## 8 2022-03-26 23:55:54 2022-03-26 23:59:17 Y Y -oth-
## 9 2022-03-26 23:59:45 2022-03-27 00:01:58 Y Y -oth-
## 10 2022-03-26 23:59:46 2022-03-27 00:02:19 Y Y -oth-
## 11 2022-03-26 23:59:47 2022-03-27 00:04:37 Y Y A1
## 12 2022-03-26 23:59:49 2022-03-27 00:03:24 Y Y A1
## 13 2022-03-26 23:59:51 2022-03-27 00:01:05 Y Y A1
## 14 2022-03-26 23:59:54 2022-03-27 00:03:45 Y Y A1
## 15 2022-03-26 23:59:56 2022-03-27 00:02:49 Y Y A1
## 16 2022-03-26 23:59:57 2022-03-27 00:01:59 Y Y A1
## 17 2022-03-26 23:59:58 2022-03-27 00:02:42 Y Y A1
## 18 2022-03-26 23:59:59 2022-03-27 00:02:30 Y Y -oth-
## 19 2022-03-27 00:00:00 2022-03-27 00:02:52 Y Y A1
## 20 2022-03-27 00:00:00 2022-03-27 00:06:20 Y Y A1
## 21 2022-03-27 00:00:02 2022-03-27 00:03:43 Y Y -oth-
## 22 2022-03-27 00:00:05 2022-03-27 00:02:40 Y Y -oth-
## 23 2022-03-27 00:00:05 2022-03-27 00:02:25 Y Y A1
## 24 2022-03-27 00:00:06 2022-03-27 00:03:30 Y Y A2
## 25 2022-03-27 00:00:09 2022-03-27 00:02:35 Y Y A2
## 26 2022-03-27 00:00:10 2022-03-27 00:02:49 Y Y A1
## 27 2022-03-27 00:00:11 2022-03-27 00:03:16 Y Y A1
## 28 2022-03-27 00:00:11 2022-03-27 00:06:24 Y Y -oth-
## 29 2022-03-27 00:00:13 2022-03-27 00:03:20 Y Y -oth-
## 30 2022-03-27 00:00:15 2022-03-27 00:04:33 Y Y A1
## 31 2022-03-27 00:00:15 2022-03-27 00:02:19 Y Y A1
## 32 2022-03-27 00:00:16 2022-03-27 00:05:25 Y Y -oth-
## 33 2022-03-27 00:00:16 2022-03-27 00:03:27 Y Y A1
## 34 2022-03-27 00:00:21 2022-03-27 00:06:14 Y Y A1
## 35 2022-03-27 00:00:25 2022-03-27 00:07:52 Y Y -oth-
## 36 2022-03-27 00:00:25 2022-03-27 00:04:09 Y Y A1
## 37 2022-03-27 00:00:25 2022-03-27 00:04:14 Y Y A1
## 38 2022-03-27 00:00:26 2022-03-27 00:02:23 Y Y A1
## 39 2022-03-27 00:00:28 2022-03-27 00:01:39 Y Y A1
## 40 2022-03-27 00:00:29 2022-03-27 00:02:30 Y Y A1
## 41 2022-03-27 00:00:30 2022-03-27 00:06:37 Y Y A1
## 42 2022-03-27 00:00:35 2022-03-27 00:02:22 Y Y -oth-
## 43 2022-03-27 00:00:42 2022-03-27 00:03:28 Y Y A1
## 44 2022-03-27 00:00:43 2022-03-27 00:06:00 Y Y A1
## 45 2022-03-27 00:01:12 2022-03-27 00:19:16 Y Y A1
## 46 2022-03-27 00:10:20 2022-03-27 00:11:57 Y Y A1
## 47 2022-03-27 00:10:24 2022-03-27 00:11:41 Y Y -oth-
## 48 2022-03-27 00:10:26 2022-03-27 00:16:18 Y Y -oth-
## 49 2022-03-27 00:10:27 2022-03-27 00:11:44 Y Y A1
## 50 2022-03-27 00:10:27 2022-03-27 00:13:52 Y Y A1
## 51 2022-03-27 00:10:27 2022-03-27 00:12:16 Y Y A1
## 52 2022-03-27 00:10:28 2022-03-27 00:13:49 Y Y A1
## 53 2022-03-27 00:10:28 2022-03-27 00:12:28 Y Y -oth-
## 54 2022-03-27 00:10:28 2022-03-27 00:12:48 Y Y A1
## 55 2022-03-27 00:10:29 2022-03-27 00:14:17 Y Y A2
## 56 2022-03-27 00:10:31 2022-03-27 00:17:16 Y Y A1
## 57 2022-03-27 00:10:32 2022-03-27 00:12:55 Y Y A2
## 58 2022-03-27 00:10:32 2022-03-27 00:23:37 Y Y A1
## 59 2022-03-27 00:10:33 2022-03-27 00:13:51 Y Y A1
## 60 2022-03-27 00:10:34 2022-03-27 00:14:14 Y Y -oth-
## 61 2022-03-27 00:10:34 2022-03-27 00:12:17 Y Y A1
## 62 2022-03-27 00:10:36 2022-03-27 00:14:03 Y Y A1
## 63 2022-03-27 00:10:36 2022-03-27 00:13:37 Y Y -oth-
## 64 2022-03-27 00:10:37 2022-03-27 00:14:39 Y Y A1
## 65 2022-03-27 00:10:37 2022-03-27 00:13:18 Y Y A1
## 66 2022-03-27 00:10:45 2022-03-27 00:19:08 Y Y -oth-
## 67 2022-03-27 00:10:54 2022-03-27 00:13:26 Y Y -oth-
## 68 2022-03-27 00:11:03 2022-03-27 00:15:51 Y Y -oth-
## 69 2022-03-27 00:12:57 2022-03-27 00:17:24 Y Y A2
## 70 2022-03-27 00:12:59 2022-03-27 00:15:03 Y Y A1
## 71 2022-03-27 00:13:00 2022-03-27 00:16:17 Y Y -oth-
## 72 2022-03-27 00:13:01 2022-03-27 00:14:21 Y Y A2
## 73 2022-03-27 00:13:02 2022-03-27 00:17:22 Y Y -oth-
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## 75 2022-03-27 00:13:04 2022-03-27 00:18:04 Y Y A1
## 76 2022-03-27 00:13:04 2022-03-27 00:15:04 Y Y A2
## 77 2022-03-27 00:13:06 2022-03-27 00:17:41 Y Y -oth-
## 78 2022-03-27 00:13:06 2022-03-27 00:15:43 Y Y A2
## 79 2022-03-27 00:13:06 2022-03-27 00:16:06 Y Y A1
## 80 2022-03-27 00:13:07 2022-03-27 00:18:20 Y Y A3
## 81 2022-03-27 00:13:09 2022-03-27 00:15:28 Y Y A1
## 82 2022-03-27 00:13:10 2022-03-27 00:17:02 Y Y A2
## 83 2022-03-27 00:13:10 2022-03-27 00:18:43 Y Y A2
## 84 2022-03-27 00:13:10 2022-03-27 00:16:21 Y Y -oth-
## 85 2022-03-27 00:13:12 2022-03-27 00:15:44 Y Y A1
## 86 2022-03-27 00:13:13 2022-03-27 00:16:21 Y Y A1
## 87 2022-03-27 00:13:15 2022-03-27 00:16:12 Y Y A1
## 88 2022-03-27 00:13:27 2022-03-27 00:16:27 Y Y A2
## 89 2022-03-27 00:13:32 2022-03-27 00:16:58 Y Y A1
## 90 2022-03-27 00:15:16 2022-03-27 00:16:19 Y Y A2
## 91 2022-03-27 00:16:53 2022-03-27 00:24:04 Y Y A2
## 92 2022-03-27 00:17:41 2022-03-27 00:31:06 Y Y -oth-
## 93 2022-03-27 00:18:10 2022-03-27 00:21:09 Y Y -oth-
## 94 2022-03-27 00:21:39 2022-03-27 00:23:49 Y Y A1
## 95 2022-03-27 00:23:08 2022-03-27 00:28:09 Y Y A1
## 96 2022-03-27 00:25:09 2022-03-27 00:26:53 Y Y -oth-
## 97 2022-03-27 00:27:58 2022-03-27 00:31:42 Y Y A1
## 98 2022-03-27 00:27:58 2022-03-27 00:30:29 Y Y A1
## 99 2022-03-27 00:27:58 2022-03-27 00:31:34 Y Y -oth-
## 100 2022-03-27 00:28:00 2022-03-27 00:30:33 Y Y -oth-
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## 109 4 6 5 6
## 110 5 6 3 3
## 111 2 2 1 1
## 112 6 2 2 2
## 113 2 2 1 1
## 114 2 1 6 6
## 115 6 3 5 4
## 116 2 4 1 1
## 117 6 6 1 1
## 118 6 2 1 1
## 119 6 1 2 4
## 120 6 2 4 3
## 121 2 2 2 2
## 122 5 3 4 4
## 123 3 4 2 2
## 124 3 2 3 5
## 125 5 2 2 4
## 126 4 2 3 5
## 127 4 3 2 2
## 128 3 2 5 6
## 129 5 5 3 2
## 130 5 6 5 4
## 131 7 7 4 2
## 132 7 4 4 2
## 133 3 6 2 3
## 134 6 6 2 3
## 135 6 6 3 3
## 136 6 6 2 3
## 137 5 5 7 4
## 138 5 7 1 1
## 139 5 3 5 3
## 140 3 3 6 5
## 141 4 3 3 3
## 142 5 5 3 3
## 143 7 3 2 2
## 144 4 2 4 5
## 145 6 4 3 3
## 146 5 4 3 2
## 147 4 6 4 4
## 148 6 6 3 3
## 149 1 1 4 4
## 150 7 5 1 1
## 151 3 3 3 2
## 152 3 2 2 3
## 153 7 7 1 4
## 154 7 5 4 4
## 155 6 3 3 3
## 156 5 4 1 1
## 157 2 2 3 3
## 158 5 5 1 2
## 159 5 3 3 4
## 160 5 4 3 5
## 161 7 6 6 7
## 162 1 1 4 4
## 163 6 6 1 1
## 164 7 4 4 2
## 165 4 3 2 2
## 166 6 6 6 4
## 167 4 1 4 4
## 168 3 3 2 2
## 169 1 6 1 1
## 170 4 5 3 3
## 171 4 4 4 3
## 172 3 3 3 3
## 173 5 6 2 5
## 174 5 5 3 3
## 175 6 5 7 5
## 176 1 1 1 1
## 177 5 6 5 3
## 178 2 2 5 4
## 179 4 4 3 4
## 180 2 2 1 1
## 181 5 3 3 3
## 182 5 3 2 2
## 183 5 7 7 4
## 184 5 4 4 3
## 185 6 5 3 2
## 186 7 6 7 5
## 187 5 5 5 5
## 188 5 6 3 3
## 189 5 6 2 2
## 190 5 3 2 2
## 191 5 6 3 5
## 192 6 4 3 3
## 193 5 2 1 3
## 194 3 2 2 4
## 195 2 4 1 1
## 196 4 5 1 1
## 197 5 6 7 5
## beamtree.pleasing. beamtree.nice. beamtree.appealing. beamtree.aesthetic.
## 1 3 3 3 3
## 2 1 1 2 1
## 3 6 6 6 6
## 4 2 2 2 1
## 5 3 3 4 6
## 6 3 2 3 4
## 7 3 6 4 5
## 8 2 2 1 1
## 9 1 2 2 2
## 10 2 3 2 2
## 11 4 4 4 4
## 12 7 7 5 6
## 13 3 2 2 2
## 14 2 2 2 2
## 15 3 5 3 3
## 16 2 2 4 2
## 17 1 1 1 1
## 18 1 1 1 1
## 19 1 2 2 4
## 20 5 5 6 3
## 21 2 3 2 2
## 22 1 1 1 1
## 23 2 3 1 1
## 24 1 1 1 1
## 25 2 3 2 2
## 26 4 5 5 4
## 27 3 2 3 2
## 28 1 3 2 3
## 29 5 5 5 5
## 30 1 1 1 1
## 31 1 1 1 1
## 32 1 3 2 5
## 33 1 1 1 1
## 34 5 3 5 6
## 35 2 2 2 1
## 36 1 2 2 3
## 37 3 3 3 5
## 38 6 4 6 6
## 39 6 6 4 5
## 40 5 3 3 1
## 41 3 3 3 3
## 42 1 1 1 1
## 43 3 5 5 4
## 44 2 3 3 2
## 45 1 3 1 2
## 46 1 1 1 1
## 47 1 1 1 1
## 48 3 2 2 4
## 49 5 5 5 4
## 50 2 2 1 2
## 51 2 5 3 6
## 52 1 2 2 2
## 53 1 1 1 1
## 54 4 5 3 5
## 55 2 2 3 3
## 56 4 5 5 4
## 57 1 1 1 1
## 58 1 1 2 2
## 59 2 2 2 2
## 60 2 2 1 1
## 61 4 5 4 3
## 62 5 4 4 3
## 63 5 5 2 4
## 64 3 4 4 2
## 65 1 1 1 1
## 66 3 3 5 6
## 67 1 3 1 1
## 68 5 5 4 4
## 69 2 1 2 3
## 70 4 5 5 5
## 71 1 2 1 1
## 72 5 5 5 5
## 73 5 4 5 3
## 74 3 5 5 4
## 75 2 3 3 3
## 76 4 5 4 5
## 77 3 5 3 5
## 78 5 6 4 6
## 79 2 3 3 1
## 80 4 5 4 6
## 81 2 2 1 5
## 82 5 4 4 4
## 83 5 6 5 6
## 84 1 1 1 1
## 85 2 3 2 3
## 86 3 3 3 2
## 87 1 1 1 5
## 88 2 3 3 4
## 89 1 4 4 4
## 90 5 4 5 4
## 91 5 5 4 4
## 92 4 5 3 3
## 93 2 5 2 2
## 94 4 3 3 3
## 95 3 3 2 1
## 96 1 1 1 1
## 97 7 6 6 6
## 98 3 2 4 3
## 99 2 2 4 4
## 100 1 1 1 1
## 101 4 6 3 2
## 102 2 2 1 2
## 103 3 5 4 6
## 104 1 1 1 1
## 105 1 3 1 1
## 106 3 3 2 3
## 107 3 2 2 1
## 108 6 6 5 4
## 109 4 3 5 5
## 110 3 4 3 3
## 111 1 2 1 2
## 112 2 3 1 1
## 113 1 1 1 1
## 114 6 6 6 7
## 115 5 5 5 7
## 116 1 1 1 1
## 117 1 2 2 3
## 118 1 1 1 1
## 119 1 3 2 5
## 120 3 3 3 4
## 121 3 2 2 2
## 122 4 4 4 5
## 123 2 2 1 3
## 124 3 4 6 4
## 125 5 2 2 2
## 126 5 4 5 3
## 127 2 2 2 2
## 128 6 6 6 6
## 129 2 2 2 2
## 130 3 4 5 5
## 131 2 5 4 2
## 132 3 3 5 3
## 133 4 3 1 3
## 134 2 2 2 2
## 135 3 4 3 3
## 136 3 3 2 5
## 137 5 6 7 3
## 138 1 1 1 1
## 139 4 4 4 5
## 140 4 4 5 5
## 141 3 2 2 2
## 142 3 3 3 3
## 143 3 3 2 2
## 144 4 7 6 6
## 145 3 4 3 3
## 146 2 2 2 4
## 147 4 4 4 5
## 148 3 3 3 6
## 149 1 4 2 2
## 150 1 1 1 1
## 151 3 3 3 2
## 152 2 2 1 3
## 153 3 7 1 4
## 154 4 4 5 3
## 155 2 4 2 2
## 156 2 1 1 1
## 157 2 2 2 1
## 158 2 2 1 2
## 159 3 3 2 3
## 160 3 4 3 4
## 161 6 7 6 7
## 162 4 4 3 3
## 163 2 1 2 1
## 164 4 4 3 5
## 165 2 2 2 1
## 166 4 6 6 6
## 167 4 4 4 4
## 168 1 2 1 1
## 169 1 1 1 4
## 170 3 3 3 3
## 171 2 3 3 2
## 172 3 3 3 3
## 173 4 4 4 5
## 174 3 3 3 3
## 175 7 7 6 6
## 176 1 1 1 1
## 177 5 5 5 4
## 178 4 4 6 3
## 179 3 3 3 3
## 180 1 1 1 1
## 181 3 4 3 4
## 182 2 3 2 2
## 183 7 7 5 7
## 184 4 4 3 5
## 185 3 3 2 5
## 186 6 7 6 7
## 187 2 5 2 5
## 188 3 4 3 4
## 189 2 2 2 2
## 190 2 2 2 2
## 191 3 2 5 5
## 192 4 3 3 4
## 193 4 2 4 1
## 194 2 3 4 6
## 195 1 1 1 1
## 196 1 1 1 1
## 197 5 6 5 6
## beamtree.pleasant. beamtree.clear. beamtree.clean. beamtree.symmetric.
## 1 3 3 3 3
## 2 1 1 1 1
## 3 6 6 6 6
## 4 2 2 3 1
## 5 2 6 1 2
## 6 3 2 3 4
## 7 3 2 6 5
## 8 2 5 5 3
## 9 1 1 3 4
## 10 3 4 2 2
## 11 4 4 5 5
## 12 7 7 6 6
## 13 2 2 2 2
## 14 2 2 5 2
## 15 3 3 6 3
## 16 2 2 2 5
## 17 2 1 1 1
## 18 1 1 1 6
## 19 1 2 1 3
## 20 3 3 5 1
## 21 3 2 2 1
## 22 1 1 1 1
## 23 1 2 3 1
## 24 1 1 1 1
## 25 2 2 3 1
## 26 5 5 3 3
## 27 3 2 2 1
## 28 2 1 2 1
## 29 5 5 5 5
## 30 1 1 1 1
## 31 1 1 1 1
## 32 1 1 1 1
## 33 1 1 1 1
## 34 4 2 3 1
## 35 2 3 3 2
## 36 2 4 3 2
## 37 3 2 2 1
## 38 6 3 6 2
## 39 5 6 5 6
## 40 2 1 3 1
## 41 3 3 3 3
## 42 1 1 1 7
## 43 5 1 5 2
## 44 3 2 2 2
## 45 1 1 7 1
## 46 1 1 1 2
## 47 1 1 1 1
## 48 3 2 3 2
## 49 4 5 5 5
## 50 2 2 2 1
## 51 4 5 5 5
## 52 2 1 3 6
## 53 1 1 1 1
## 54 4 6 6 1
## 55 3 1 3 1
## 56 4 3 5 3
## 57 1 1 1 1
## 58 1 1 2 2
## 59 1 1 2 4
## 60 2 4 1 1
## 61 5 4 5 2
## 62 5 2 2 5
## 63 4 6 6 7
## 64 3 4 5 5
## 65 1 1 1 1
## 66 2 4 1 1
## 67 2 2 1 2
## 68 5 2 4 2
## 69 2 3 3 2
## 70 4 4 5 4
## 71 1 1 1 3
## 72 5 4 5 6
## 73 5 4 4 2
## 74 5 2 2 2
## 75 1 1 4 3
## 76 4 2 5 1
## 77 3 4 3 1
## 78 5 2 1 5
## 79 2 2 2 6
## 80 4 2 3 3
## 81 2 5 4 4
## 82 5 3 5 3
## 83 5 6 6 1
## 84 1 1 1 1
## 85 2 1 1 1
## 86 3 3 3 3
## 87 1 1 1 1
## 88 2 1 5 3
## 89 4 6 2 3
## 90 5 2 5 1
## 91 4 5 5 6
## 92 4 5 5 5
## 93 2 4 5 3
## 94 4 3 3 5
## 95 1 3 5 1
## 96 1 1 1 1
## 97 6 2 5 7
## 98 4 3 4 2
## 99 2 1 4 1
## 100 1 1 1 1
## 101 2 6 7 6
## 102 2 2 2 4
## 103 5 2 2 6
## 104 1 1 1 2
## 105 1 4 5 2
## 106 3 1 5 6
## 107 2 2 1 2
## 108 6 3 4 2
## 109 4 2 3 3
## 110 4 1 4 3
## 111 1 1 1 3
## 112 1 1 2 1
## 113 1 1 1 1
## 114 6 6 5 5
## 115 5 6 6 4
## 116 1 1 1 1
## 117 1 1 2 2
## 118 1 1 1 1
## 119 3 1 1 1
## 120 3 3 3 2
## 121 2 3 2 3
## 122 4 5 5 5
## 123 2 1 1 2
## 124 4 3 4 4
## 125 5 2 2 1
## 126 5 3 3 4
## 127 2 1 2 2
## 128 6 6 6 6
## 129 3 1 2 2
## 130 4 2 1 1
## 131 2 6 4 6
## 132 2 2 6 4
## 133 2 2 3 7
## 134 2 3 3 1
## 135 3 2 3 2
## 136 3 1 4 2
## 137 5 5 5 4
## 138 1 1 1 1
## 139 3 2 2 3
## 140 3 1 2 3
## 141 2 2 2 2
## 142 3 3 3 3
## 143 4 2 1 5
## 144 4 6 7 4
## 145 2 1 4 5
## 146 2 4 5 5
## 147 4 4 4 6
## 148 2 3 3 2
## 149 2 3 2 1
## 150 1 3 6 1
## 151 3 4 3 2
## 152 3 2 1 2
## 153 3 4 3 5
## 154 4 1 3 1
## 155 2 3 6 2
## 156 1 1 2 1
## 157 2 1 1 1
## 158 2 1 3 2
## 159 3 5 5 1
## 160 3 4 5 4
## 161 7 7 7 6
## 162 3 3 3 3
## 163 2 5 1 5
## 164 3 2 5 2
## 165 2 2 2 1
## 166 4 2 6 5
## 167 4 6 4 1
## 168 1 2 2 2
## 169 1 1 5 5
## 170 3 2 5 5
## 171 3 3 4 5
## 172 3 2 3 3
## 173 3 1 4 4
## 174 3 3 3 3
## 175 5 6 6 7
## 176 1 1 1 5
## 177 5 4 4 4
## 178 4 6 4 3
## 179 4 4 3 3
## 180 1 1 1 1
## 181 3 3 4 3
## 182 2 4 4 1
## 183 6 1 1 5
## 184 4 2 4 3
## 185 3 2 2 1
## 186 5 7 5 7
## 187 2 2 2 2
## 188 3 3 3 2
## 189 2 2 2 2
## 190 2 2 2 4
## 191 2 3 3 5
## 192 3 2 2 1
## 193 3 2 2 2
## 194 4 2 5 3
## 195 1 1 1 1
## 196 1 1 2 1
## 197 6 7 6 7
## startree.enjoyable. startree.likable. startree.pleasing. startree.nice.
## 1 4 4 3 3
## 2 2 2 1 2
## 3 3 3 3 3
## 4 5 5 5 5
## 5 4 5 5 2
## 6 3 5 4 5
## 7 7 7 6 6
## 8 3 3 1 5
## 9 4 5 3 3
## 10 5 4 4 5
## 11 2 2 2 2
## 12 5 6 6 6
## 13 3 5 2 3
## 14 3 3 2 3
## 15 2 2 2 3
## 16 2 3 2 2
## 17 7 6 6 6
## 18 4 2 2 4
## 19 5 5 4 5
## 20 7 7 6 7
## 21 5 5 5 6
## 22 1 1 1 1
## 23 6 4 5 4
## 24 1 2 1 2
## 25 4 3 3 4
## 26 2 2 2 2
## 27 6 5 5 5
## 28 5 5 3 6
## 29 6 6 6 6
## 30 4 5 4 6
## 31 3 3 3 3
## 32 2 1 1 1
## 33 3 3 3 3
## 34 7 7 7 7
## 35 5 5 4 5
## 36 4 3 2 1
## 37 5 5 4 5
## 38 4 2 2 2
## 39 6 6 4 6
## 40 3 5 3 5
## 41 5 5 3 5
## 42 1 1 1 4
## 43 5 5 3 5
## 44 3 3 3 3
## 45 3 3 1 1
## 46 1 2 1 1
## 47 1 1 1 1
## 48 6 6 6 6
## 49 3 4 4 2
## 50 4 5 5 3
## 51 3 2 3 4
## 52 4 4 3 4
## 53 4 5 4 5
## 54 6 5 4 3
## 55 5 5 5 5
## 56 5 3 3 3
## 57 4 4 4 4
## 58 4 4 3 4
## 59 2 4 4 4
## 60 7 7 7 7
## 61 3 5 3 4
## 62 5 3 2 3
## 63 2 3 3 4
## 64 5 4 2 4
## 65 5 5 5 5
## 66 5 4 5 6
## 67 5 6 4 5
## 68 5 5 5 6
## 69 3 2 2 3
## 70 4 3 4 5
## 71 5 5 3 5
## 72 1 4 1 4
## 73 3 3 3 3
## 74 5 4 5 5
## 75 5 4 3 5
## 76 4 4 5 5
## 77 3 3 3 4
## 78 6 4 5 5
## 79 5 5 5 4
## 80 4 5 4 5
## 81 2 1 1 3
## 82 3 3 3 3
## 83 6 6 5 5
## 84 1 1 1 1
## 85 6 7 6 6
## 86 4 4 4 4
## 87 5 5 5 5
## 88 4 4 2 4
## 89 3 3 3 2
## 90 4 5 5 5
## 91 3 4 5 4
## 92 5 5 5 5
## 93 5 6 6 5
## 94 4 5 5 4
## 95 2 3 4 3
## 96 2 3 3 4
## 97 7 7 7 6
## 98 5 5 4 5
## 99 3 4 5 4
## 100 5 5 6 6
## 101 5 5 2 6
## 102 3 5 5 4
## 103 6 6 5 6
## 104 1 3 4 1
## 105 6 6 6 6
## 106 5 5 4 4
## 107 5 4 3 3
## 108 3 3 5 3
## 109 2 3 2 2
## 110 4 5 4 4
## 111 4 4 4 4
## 112 7 6 6 6
## 113 1 1 1 1
## 114 1 1 1 1
## 115 3 2 2 1
## 116 5 5 5 5
## 117 1 2 1 3
## 118 2 1 1 1
## 119 5 6 6 5
## 120 4 5 5 5
## 121 1 1 1 1
## 122 5 4 4 4
## 123 2 2 2 2
## 124 4 4 7 3
## 125 4 5 5 5
## 126 4 3 3 2
## 127 4 4 4 4
## 128 6 5 5 5
## 129 4 5 4 4
## 130 2 3 2 3
## 131 5 5 5 6
## 132 6 6 6 6
## 133 6 5 5 6
## 134 5 5 5 5
## 135 5 6 6 5
## 136 4 4 4 5
## 137 2 3 2 2
## 138 2 6 5 5
## 139 3 2 2 3
## 140 2 3 3 3
## 141 3 3 3 3
## 142 5 5 4 4
## 143 5 5 5 4
## 144 2 1 1 3
## 145 2 3 2 3
## 146 2 2 2 2
## 147 3 4 3 3
## 148 5 4 5 5
## 149 5 5 5 6
## 150 1 2 1 1
## 151 3 3 3 2
## 152 6 5 7 6
## 153 4 5 4 4
## 154 4 2 3 2
## 155 4 4 4 5
## 156 1 3 2 3
## 157 3 4 4 3
## 158 4 4 3 5
## 159 2 1 2 3
## 160 3 4 3 4
## 161 6 6 6 6
## 162 6 6 6 6
## 163 5 5 3 5
## 164 4 6 5 6
## 165 6 6 5 5
## 166 2 4 1 2
## 167 3 3 3 1
## 168 3 5 3 3
## 169 3 4 4 3
## 170 5 6 6 6
## 171 2 3 4 3
## 172 3 3 3 3
## 173 4 4 5 4
## 174 5 5 5 5
## 175 5 6 5 6
## 176 1 1 1 1
## 177 6 5 6 6
## 178 2 3 4 4
## 179 5 5 5 4
## 180 3 3 2 2
## 181 4 6 4 5
## 182 4 4 4 5
## 183 5 3 4 3
## 184 4 4 3 4
## 185 5 5 5 5
## 186 2 2 2 3
## 187 2 2 2 2
## 188 5 4 4 5
## 189 4 5 5 5
## 190 1 1 1 1
## 191 1 1 1 1
## 192 4 4 4 4
## 193 4 4 4 6
## 194 1 4 2 4
## 195 1 1 1 1
## 196 4 3 3 3
## 197 6 7 6 6
## startree.appealing. startree.aesthetic. startree.pleasant. startree.clear.
## 1 3 4 4 5
## 2 3 1 1 4
## 3 3 2 2 3
## 4 5 3 5 5
## 5 5 4 4 4
## 6 5 2 4 5
## 7 6 7 6 6
## 8 1 3 2 4
## 9 2 2 2 6
## 10 5 5 4 5
## 11 2 2 3 2
## 12 5 7 6 4
## 13 3 3 3 2
## 14 3 2 4 3
## 15 2 1 2 5
## 16 2 1 2 1
## 17 7 6 6 7
## 18 2 2 3 6
## 19 4 5 5 3
## 20 6 7 7 7
## 21 5 4 6 6
## 22 1 1 1 1
## 23 5 3 4 7
## 24 1 2 1 1
## 25 3 3 3 6
## 26 2 1 2 2
## 27 5 4 5 5
## 28 4 5 4 3
## 29 6 6 6 6
## 30 4 2 4 4
## 31 3 3 3 3
## 32 1 1 1 1
## 33 3 2 3 3
## 34 7 7 7 7
## 35 5 5 6 6
## 36 3 2 3 4
## 37 4 5 4 5
## 38 2 2 3 5
## 39 6 6 5 6
## 40 5 6 6 6
## 41 3 3 3 3
## 42 3 1 3 1
## 43 4 3 4 6
## 44 3 3 3 3
## 45 2 3 1 1
## 46 1 3 1 1
## 47 1 1 1 1
## 48 6 5 6 7
## 49 3 4 3 2
## 50 3 5 5 5
## 51 3 3 2 5
## 52 5 2 3 6
## 53 5 5 4 5
## 54 2 5 5 6
## 55 4 6 4 5
## 56 5 5 3 5
## 57 4 4 4 5
## 58 5 3 4 6
## 59 2 2 3 5
## 60 7 6 7 5
## 61 4 3 5 2
## 62 4 1 1 6
## 63 3 2 3 4
## 64 4 2 3 3
## 65 3 4 4 5
## 66 5 5 5 4
## 67 4 7 2 2
## 68 6 6 5 5
## 69 2 1 2 4
## 70 3 4 5 4
## 71 5 5 5 3
## 72 4 2 1 1
## 73 3 3 3 4
## 74 5 3 5 6
## 75 3 4 3 2
## 76 4 5 5 4
## 77 2 3 3 5
## 78 5 3 5 7
## 79 5 6 5 3
## 80 4 4 3 6
## 81 1 1 2 6
## 82 3 2 3 4
## 83 5 6 5 5
## 84 1 1 1 1
## 85 5 3 5 7
## 86 4 4 4 5
## 87 5 3 5 6
## 88 3 3 2 2
## 89 4 4 3 5
## 90 4 5 4 4
## 91 4 3 4 5
## 92 5 3 5 3
## 93 6 2 6 6
## 94 4 3 5 5
## 95 2 1 4 5
## 96 5 2 2 5
## 97 7 7 6 4
## 98 3 4 4 5
## 99 3 5 4 6
## 100 5 5 5 4
## 101 2 2 3 1
## 102 5 3 4 7
## 103 6 6 5 4
## 104 4 2 2 5
## 105 6 5 6 6
## 106 3 5 5 3
## 107 5 2 3 5
## 108 6 5 3 5
## 109 3 1 2 6
## 110 3 4 4 6
## 111 4 4 4 2
## 112 6 7 6 5
## 113 1 2 2 1
## 114 1 7 1 1
## 115 3 2 3 1
## 116 5 5 5 5
## 117 1 2 1 3
## 118 1 1 1 4
## 119 6 6 5 7
## 120 6 4 4 2
## 121 1 1 1 1
## 122 3 4 4 4
## 123 2 2 2 3
## 124 1 7 5 1
## 125 5 3 5 5
## 126 2 2 3 5
## 127 4 4 4 5
## 128 5 3 5 6
## 129 5 5 4 5
## 130 2 2 4 1
## 131 6 7 4 7
## 132 6 5 7 7
## 133 5 4 5 5
## 134 5 5 5 5
## 135 6 4 6 5
## 136 3 4 3 6
## 137 3 1 3 3
## 138 6 3 3 5
## 139 3 3 2 2
## 140 3 1 2 2
## 141 3 4 4 5
## 142 4 4 5 2
## 143 5 5 4 6
## 144 1 2 1 2
## 145 3 2 3 1
## 146 2 2 2 2
## 147 5 4 3 5
## 148 5 6 5 3
## 149 6 6 6 5
## 150 1 1 1 1
## 151 2 1 3 3
## 152 7 6 6 5
## 153 7 3 6 5
## 154 4 1 3 3
## 155 4 5 4 3
## 156 1 3 1 1
## 157 3 3 3 2
## 158 3 2 2 3
## 159 2 2 3 5
## 160 3 5 3 3
## 161 6 6 6 7
## 162 5 6 6 6
## 163 5 5 3 2
## 164 6 7 6 6
## 165 3 4 5 5
## 166 4 1 1 1
## 167 3 3 4 3
## 168 1 5 3 2
## 169 2 5 5 5
## 170 6 5 6 6
## 171 4 3 4 4
## 172 3 3 3 3
## 173 4 5 6 5
## 174 5 4 5 5
## 175 7 4 5 7
## 176 1 1 1 1
## 177 6 5 5 5
## 178 3 5 3 3
## 179 4 5 4 4
## 180 2 1 3 3
## 181 4 5 4 5
## 182 5 4 5 4
## 183 5 6 2 1
## 184 3 4 3 4
## 185 5 5 5 6
## 186 5 4 1 3
## 187 2 2 2 2
## 188 4 5 4 4
## 189 5 4 4 5
## 190 1 1 1 1
## 191 1 1 1 1
## 192 4 5 4 5
## 193 3 3 5 5
## 194 2 2 2 1
## 195 1 1 1 1
## 196 5 3 4 5
## 197 5 5 5 6
## startree.clean. startree.symmetric. startree.agree.
## 1 3 5 6
## 2 2 1 6
## 3 2 2 6
## 4 5 2 6
## 5 4 4 6
## 6 4 2 6
## 7 7 6 6
## 8 2 3 6
## 9 3 1 6
## 10 4 5 6
## 11 2 3 6
## 12 7 5 6
## 13 3 2 6
## 14 2 2 6
## 15 4 2 6
## 16 1 2 6
## 17 6 1 6
## 18 5 1 6
## 19 4 2 6
## 20 7 4 6
## 21 4 1 6
## 22 1 1 6
## 23 3 2 6
## 24 1 1 6
## 25 3 1 6
## 26 2 2 6
## 27 5 5 6
## 28 4 2 6
## 29 6 6 6
## 30 4 2 6
## 31 3 3 6
## 32 1 1 6
## 33 3 4 6
## 34 7 5 6
## 35 6 2 6
## 36 3 2 6
## 37 5 1 6
## 38 2 1 6
## 39 6 6 6
## 40 3 6 6
## 41 3 2 6
## 42 1 1 6
## 43 3 1 6
## 44 2 3 6
## 45 1 1 6
## 46 1 6 6
## 47 1 1 6
## 48 7 6 6
## 49 3 2 6
## 50 3 2 6
## 51 5 6 6
## 52 5 6 6
## 53 5 4 6
## 54 3 4 6
## 55 3 3 6
## 56 3 2 6
## 57 5 2 6
## 58 5 2 6
## 59 5 1 6
## 60 6 7 6
## 61 2 3 6
## 62 2 1 6
## 63 2 5 6
## 64 4 3 6
## 65 4 2 6
## 66 1 3 6
## 67 1 1 6
## 68 5 4 6
## 69 2 1 6
## 70 4 4 6
## 71 3 5 6
## 72 2 1 6
## 73 3 1 6
## 74 5 2 6
## 75 4 2 6
## 76 4 1 6
## 77 3 1 6
## 78 4 6 6
## 79 2 6 6
## 80 2 3 6
## 81 1 2 6
## 82 2 3 6
## 83 6 1 6
## 84 1 1 6
## 85 6 4 6
## 86 5 4 6
## 87 6 2 6
## 88 3 2 6
## 89 3 3 6
## 90 5 2 6
## 91 4 3 6
## 92 3 3 6
## 93 6 2 6
## 94 5 2 6
## 95 5 1 6
## 96 5 1 6
## 97 5 3 6
## 98 6 2 6
## 99 5 1 6
## 100 6 2 6
## 101 2 1 6
## 102 6 3 6
## 103 3 2 6
## 104 5 3 6
## 105 3 3 6
## 106 3 2 6
## 107 3 2 6
## 108 5 6 6
## 109 5 4 6
## 110 6 4 6
## 111 4 2 6
## 112 7 2 6
## 113 1 1 6
## 114 1 1 6
## 115 2 2 6
## 116 4 2 6
## 117 2 2 6
## 118 1 1 6
## 119 3 1 6
## 120 4 3 6
## 121 1 1 6
## 122 5 5 6
## 123 2 2 6
## 124 1 1 6
## 125 3 3 6
## 126 3 4 6
## 127 4 2 6
## 128 5 2 6
## 129 6 4 6
## 130 1 3 6
## 131 6 6 6
## 132 7 5 6
## 133 6 2 6
## 134 2 3 6
## 135 6 3 6
## 136 6 3 6
## 137 2 4 6
## 138 7 2 6
## 139 2 1 6
## 140 4 1 6
## 141 3 4 6
## 142 4 5 6
## 143 3 3 6
## 144 1 1 6
## 145 2 2 6
## 146 1 1 6
## 147 2 3 6
## 148 3 2 6
## 149 4 1 6
## 150 2 1 6
## 151 2 1 6
## 152 6 3 6
## 153 7 5 6
## 154 3 1 6
## 155 2 2 6
## 156 3 1 6
## 157 3 2 6
## 158 4 3 6
## 159 6 1 6
## 160 3 2 6
## 161 7 6 6
## 162 6 3 6
## 163 2 2 6
## 164 6 2 6
## 165 3 2 6
## 166 1 1 6
## 167 3 1 6
## 168 2 2 6
## 169 6 3 6
## 170 6 5 6
## 171 2 2 6
## 172 3 3 6
## 173 5 6 6
## 174 6 4 6
## 175 7 5 6
## 176 1 3 6
## 177 5 6 6
## 178 3 4 6
## 179 5 5 6
## 180 2 1 6
## 181 5 2 6
## 182 4 4 6
## 183 1 1 6
## 184 5 3 6
## 185 4 5 6
## 186 2 1 6
## 187 2 2 6
## 188 5 2 6
## 189 4 3 6
## 190 1 3 6
## 191 1 1 6
## 192 3 2 6
## 193 4 2 6
## 194 1 1 6
## 195 1 1 6
## 196 4 3 6
## 197 5 6 6
## END
## 1
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19 No.
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27 None, thanks!
## 28
## 29
## 30 I don't have any
## 31
## 32
## 33
## 34
## 35 I don't have any comments.
## 36
## 37
## 38
## 39
## 40
## 41
## 42
## 43
## 44 Although the yellow-ish color scheme is overall pleasant I think another colour scheme would make it more aesthetically pleasing, yellow can is a safe colour but it can be boring. I think a nice shade of green or even a blue (but tinted more green or lilac for example) could perhaps be more pleasing to the eye.
## 45
## 46
## 47
## 48 I think you should add other academic degrees if you're asking about it, not everyone has finished university.
## 49
## 50
## 51
## 52
## 53
## 54
## 55 No
## 56
## 57
## 58
## 59
## 60
## 61
## 62
## 63
## 64 I don't have any comments about this survey
## 65
## 66
## 67
## 68
## 69
## 70 Nice studie
## 71
## 72
## 73
## 74
## 75 Thank you for the survey. :)
## 76
## 77
## 78
## 79
## 80
## 81
## 82
## 83
## 84
## 85
## 86
## 87
## 88
## 89
## 90
## 91
## 92
## 93
## 94
## 95
## 96
## 97
## 98
## 99
## 100
## 101
## 102
## 103
## 104
## 105
## 106
## 107
## 108 none
## 109
## 110
## 111 thanks
## 112
## 113 Thank you for letting me participate\n
## 114
## 115 I have no comments.
## 116
## 117
## 118
## 119
## 120
## 121
## 122
## 123
## 124
## 125
## 126
## 127 No comments
## 128
## 129
## 130
## 131
## 132 All good.
## 133
## 134
## 135
## 136
## 137
## 138
## 139
## 140
## 141
## 142
## 143
## 144
## 145
## 146
## 147 Nope.
## 148
## 149
## 150
## 151
## 152
## 153 The tube chart could have been more appealing if the edges weren't too jagged to be honest
## 154
## 155
## 156
## 157
## 158
## 159
## 160
## 161 No comment.
## 162
## 163
## 164
## 165
## 166
## 167
## 168
## 169
## 170 No comments.
## 171
## 172
## 173
## 174 none
## 175
## 176 Thank you for allowing me to participate in this study! I wish you success :)
## 177
## 178
## 179
## 180
## 181 no
## 182
## 183
## 184
## 185
## 186
## 187
## 188
## 189
## 190
## 191
## 192
## 193
## 194
## 195
## 196
## 197
## interviewtime groupTime7643 PIDTime CF001Time CF002Time groupTime7644
## 1 109.50 17.31 NA NA NA 15.39
## 2 151.55 8.30 NA NA NA 16.84
## 3 134.06 20.40 NA NA NA 10.04
## 4 145.53 13.69 NA NA NA 13.85
## 5 129.74 9.75 NA NA NA 5.06
## 6 268.15 13.24 NA NA NA 10.41
## 7 329.84 70.99 NA NA NA 11.15
## 8 206.77 26.38 NA NA NA 21.31
## 9 135.91 15.12 NA NA NA 15.22
## 10 155.74 11.59 NA NA NA 17.69
## 11 293.64 8.89 NA NA NA 7.61
## 12 218.47 33.57 NA NA NA 8.79
## 13 75.28 10.95 NA NA NA 4.80
## 14 233.46 35.14 NA NA NA 10.20
## 15 174.67 27.20 NA NA NA 6.70
## 16 125.49 11.73 NA NA NA 8.48
## 17 165.88 67.60 NA NA NA 5.15
## 18 154.72 14.03 NA NA NA 22.86
## 19 174.20 41.88 NA NA NA 13.46
## 20 381.70 262.39 NA NA NA 5.82
## 21 225.61 52.35 NA NA NA 24.44
## 22 157.61 50.82 NA NA NA 25.67
## 23 143.05 29.54 NA NA NA 5.42
## 24 207.64 36.19 NA NA NA 7.02
## 25 148.72 26.85 NA NA NA 7.97
## 26 161.36 20.76 NA NA NA 6.58
## 27 187.84 29.39 NA NA NA 8.15
## 28 375.87 171.60 NA NA NA 20.57
## 29 190.58 95.58 NA NA NA 16.80
## 30 259.01 68.46 NA NA NA 10.98
## 31 125.80 7.84 NA NA NA 5.39
## 32 317.58 29.81 NA NA NA 34.80
## 33 194.09 26.97 NA NA NA 8.81
## 34 357.13 109.79 NA NA NA 98.08
## 35 449.45 143.44 NA NA NA 45.48
## 36 227.93 70.60 NA NA NA 4.56
## 37 231.62 31.48 NA NA NA 8.11
## 38 120.84 14.40 NA NA NA 6.49
## 39 76.21 8.10 NA NA NA 9.80
## 40 124.20 15.80 NA NA NA 7.51
## 41 371.62 51.70 NA NA NA 10.92
## 42 109.40 6.89 NA NA NA 10.79
## 43 168.51 29.23 NA NA NA 6.62
## 44 319.25 37.34 NA NA NA 6.57
## 45 1087.81 452.49 NA NA NA 6.97
## 46 100.69 15.98 NA NA NA 5.67
## 47 79.84 9.48 NA NA NA 11.30
## 48 354.39 42.22 NA NA NA 51.59
## 49 81.16 9.84 NA NA NA 8.22
## 50 208.89 22.90 NA NA NA 7.48
## 51 113.54 17.77 NA NA NA 12.24
## 52 204.47 55.84 NA NA NA 13.31
## 53 123.52 20.73 NA NA NA 23.10
## 54 143.97 9.20 NA NA NA 5.73
## 55 231.49 27.16 NA NA NA 5.64
## 56 407.10 34.61 NA NA NA 5.43
## 57 145.96 19.06 NA NA NA 3.52
## 58 787.98 650.54 NA NA NA 6.58
## 59 201.34 37.87 NA NA NA 5.62
## 60 224.37 73.54 NA NA NA 30.84
## 61 106.22 14.45 NA NA NA 4.54
## 62 209.76 46.14 NA NA NA 6.81
## 63 184.48 25.26 NA NA NA 24.89
## 64 244.10 45.17 NA NA NA 6.93
## 65 163.73 13.98 NA NA NA 4.74
## 66 506.57 266.51 NA NA NA 26.21
## 67 154.38 34.30 NA NA NA 13.38
## 68 291.21 25.52 NA NA NA 101.35
## 69 270.14 57.62 NA NA NA 6.93
## 70 126.74 65.75 NA NA NA 6.31
## 71 201.15 45.95 NA NA NA 11.40
## 72 84.26 6.48 NA NA NA 7.79
## 73 263.45 18.28 NA NA NA 125.44
## 74 105.43 10.45 NA NA NA 4.27
## 75 304.80 55.58 NA NA NA 9.62
## 76 123.78 7.42 NA NA NA 9.91
## 77 278.59 60.36 NA NA NA 25.95
## 78 160.54 11.43 NA NA NA 4.99
## 79 182.49 11.69 NA NA NA 11.41
## 80 315.31 110.50 NA NA NA 7.97
## 81 143.37 10.36 NA NA NA 11.24
## 82 235.41 43.06 NA NA NA 6.85
## 83 335.68 80.21 NA NA NA 8.46
## 84 194.83 49.19 NA NA NA 12.40
## 85 154.52 28.18 NA NA NA 7.60
## 86 191.26 50.16 NA NA NA 4.31
## 87 180.27 53.73 NA NA NA 9.36
## 88 182.21 55.74 NA NA NA 7.32
## 89 209.57 18.83 NA NA NA 10.16
## 90 66.30 7.10 NA NA NA 2.68
## 91 433.19 122.33 NA NA NA 9.11
## 92 750.43 23.32 NA NA NA 114.18
## 93 181.60 12.82 NA NA NA 22.59
## 94 132.52 17.79 NA NA NA 8.47
## 95 305.18 27.72 NA NA NA 10.13
## 96 107.33 19.13 NA NA NA 29.86
## 97 192.58 40.30 NA NA NA 17.15
## 98 137.87 11.25 NA NA NA 5.40
## 99 220.77 80.52 NA NA NA 12.84
## 100 134.79 10.14 NA NA NA 11.25
## 101 193.78 35.28 NA NA NA 15.64
## 102 415.10 265.56 NA NA NA 23.38
## 103 125.25 18.58 NA NA NA 11.95
## 104 197.13 47.62 NA NA NA 5.53
## 105 135.39 23.60 NA NA NA 10.05
## 106 226.96 45.63 NA NA NA 40.27
## 107 201.69 29.96 NA NA NA 11.02
## 108 315.78 38.17 NA NA NA 8.56
## 109 170.06 32.72 NA NA NA 10.92
## 110 130.98 13.68 NA NA NA 19.31
## 111 203.20 18.46 NA NA NA 16.31
## 112 145.23 24.99 NA NA NA 11.17
## 113 141.08 16.36 NA NA NA 10.31
## 114 361.77 33.51 NA NA NA 93.42
## 115 156.74 15.49 NA NA NA 12.66
## 116 123.38 19.18 NA NA NA 11.07
## 117 180.22 22.86 NA NA NA 15.33
## 118 229.21 77.59 NA NA NA 41.04
## 119 210.67 34.04 NA NA NA 11.33
## 120 161.05 22.85 NA NA NA 8.24
## 121 151.12 32.39 NA NA NA 6.72
## 122 162.22 17.68 NA NA NA 11.14
## 123 374.67 61.79 NA NA NA 55.26
## 124 103.96 16.60 NA NA NA 13.11
## 125 208.08 24.28 NA NA NA 9.27
## 126 128.35 18.77 NA NA NA 7.02
## 127 177.84 37.15 NA NA NA 18.12
## 128 624.04 15.61 NA NA NA 18.38
## 129 211.50 21.54 NA NA NA 35.24
## 130 261.32 73.53 NA NA NA 11.85
## 131 163.54 32.85 NA NA NA 6.88
## 132 607.75 95.12 NA NA NA 19.88
## 133 238.96 49.02 NA NA NA 15.76
## 134 172.52 33.38 NA NA NA 26.00
## 135 201.53 21.82 NA NA NA 11.01
## 136 218.02 46.12 NA NA NA 7.33
## 137 136.82 43.01 NA NA NA 11.55
## 138 296.59 18.48 NA NA NA 20.46
## 139 175.30 16.24 NA NA NA 7.64
## 140 182.73 28.56 NA NA NA 10.05
## 141 265.72 35.69 NA NA NA 14.74
## 142 187.38 34.95 NA NA NA 5.08
## 143 137.03 20.65 NA NA NA 6.08
## 144 386.70 148.84 NA NA NA 9.50
## 145 160.05 13.00 NA NA NA 5.64
## 146 157.19 12.39 NA NA NA 29.68
## 147 439.99 93.83 NA NA NA 10.97
## 148 133.87 10.79 NA NA NA 4.40
## 149 163.31 18.88 NA NA NA 12.34
## 150 168.09 12.19 NA NA NA 30.59
## 151 171.81 33.08 NA NA NA 7.22
## 152 216.62 15.71 NA NA NA 4.50
## 153 356.19 31.08 NA NA NA 14.49
## 154 191.24 30.08 NA NA NA 5.47
## 155 166.12 31.17 NA NA NA 11.89
## 156 125.78 9.89 NA NA NA 8.48
## 157 207.88 52.67 NA NA NA 29.27
## 158 148.68 26.53 NA NA NA 6.83
## 159 318.91 52.82 NA NA NA 32.88
## 160 120.10 21.01 NA NA NA 8.05
## 161 325.75 101.94 NA NA NA 9.84
## 162 180.83 17.59 NA NA NA 14.62
## 163 435.68 55.91 NA NA NA 11.59
## 164 185.74 15.08 NA NA NA 14.41
## 165 106.36 12.33 NA NA NA 3.93
## 166 510.35 60.97 NA NA NA 8.22
## 167 458.72 21.08 NA NA NA 29.73
## 168 242.66 13.94 NA NA NA 12.43
## 169 273.65 69.38 NA NA NA 14.29
## 170 390.53 45.11 NA NA NA 12.06
## 171 143.33 13.39 NA NA NA 7.41
## 172 165.28 33.63 NA NA NA 12.54
## 173 540.00 213.45 NA NA NA 13.08
## 174 119.28 14.65 NA NA NA 4.93
## 175 127.15 28.96 NA NA NA 11.42
## 176 172.01 49.42 NA NA NA 4.22
## 177 790.49 7.95 NA NA NA 17.70
## 178 139.71 16.65 NA NA NA 17.88
## 179 84.01 11.72 NA NA NA 6.14
## 180 172.10 18.98 NA NA NA 9.80
## 181 580.59 226.98 NA NA NA 68.01
## 182 236.08 57.74 NA NA NA 6.80
## 183 316.59 70.04 NA NA NA 72.58
## 184 274.04 22.87 NA NA NA 48.74
## 185 290.01 96.44 NA NA NA 21.34
## 186 117.72 10.33 NA NA NA 7.69
## 187 169.61 19.83 NA NA NA 70.94
## 188 116.30 11.19 NA NA NA 4.05
## 189 80.92 14.04 NA NA NA 5.92
## 190 103.89 18.87 NA NA NA 6.82
## 191 125.62 8.72 NA NA NA 6.43
## 192 143.19 11.58 NA NA NA 10.10
## 193 192.35 35.61 NA NA NA 10.46
## 194 296.22 50.05 NA NA NA 43.93
## 195 218.48 59.60 NA NA NA 6.54
## 196 178.19 13.17 NA NA NA 33.05
## 197 62.63 10.13 NA NA NA 5.54
## educationTime groupTime7645 IQ001Time groupTime7647 sunburstTime
## 1 NA 12.30 NA 25.35 NA
## 2 NA 38.18 NA 31.52 NA
## 3 NA 25.48 NA 24.33 NA
## 4 NA 28.33 NA 41.48 NA
## 5 NA 20.01 NA 39.05 NA
## 6 NA 31.05 NA 60.73 NA
## 7 NA 84.28 NA 53.80 NA
## 8 NA 45.37 NA 35.73 NA
## 9 NA 28.84 NA 20.84 NA
## 10 NA 28.79 NA 28.43 NA
## 11 NA 219.68 NA 15.10 NA
## 12 NA 44.29 NA 29.80 NA
## 13 NA 4.49 NA 21.36 NA
## 14 NA 59.14 NA 30.25 NA
## 15 NA 54.52 NA 20.35 NA
## 16 NA 54.69 NA 13.09 NA
## 17 NA 21.02 NA 29.28 NA
## 18 NA 46.36 NA 23.23 NA
## 19 NA 41.97 NA 24.24 NA
## 20 NA 27.33 NA 38.03 NA
## 21 NA 35.22 NA 28.94 NA
## 22 NA 32.88 NA 19.16 NA
## 23 NA 30.19 NA 20.36 NA
## 24 NA 55.50 NA 28.32 NA
## 25 NA 29.88 NA 19.30 NA
## 26 NA 36.08 NA 30.75 NA
## 27 NA 28.59 NA 36.65 NA
## 28 NA 62.56 NA 43.24 NA
## 29 NA 6.00 NA 21.47 NA
## 30 NA 38.12 NA 41.01 NA
## 31 NA 38.24 NA 13.20 NA
## 32 NA 144.97 NA 25.85 NA
## 33 NA 24.24 NA 28.26 NA
## 34 NA 26.75 NA 51.63 NA
## 35 NA 60.10 NA 28.80 NA
## 36 NA 38.95 NA 38.57 NA
## 37 NA 55.22 NA 85.37 NA
## 38 NA 13.58 NA 25.83 NA
## 39 NA 4.32 NA 15.65 NA
## 40 NA 5.85 NA 28.89 NA
## 41 NA 156.93 NA 47.45 NA
## 42 NA 42.52 NA 14.40 NA
## 43 NA 25.17 NA 40.08 NA
## 44 NA 34.13 NA 40.06 NA
## 45 NA 112.31 NA 40.00 NA
## 46 NA 17.85 NA 16.48 NA
## 47 NA 10.79 NA 19.18 NA
## 48 NA 34.27 NA 48.15 NA
## 49 NA 3.74 NA 18.65 NA
## 50 NA 62.78 NA 22.64 NA
## 51 NA 18.68 NA 16.83 NA
## 52 NA 26.80 NA 30.87 NA
## 53 NA 20.41 NA 22.39 NA
## 54 NA 5.48 NA 29.40 NA
## 55 NA 39.76 NA 48.52 NA
## 56 NA 117.95 NA 150.04 NA
## 57 NA 33.11 NA 27.37 NA
## 58 NA 21.99 NA 35.09 NA
## 59 NA 46.47 NA 26.04 NA
## 60 NA 29.77 NA 29.17 NA
## 61 NA 27.74 NA 12.22 NA
## 62 NA 51.22 NA 29.04 NA
## 63 NA 18.27 NA 11.89 NA
## 64 NA 69.00 NA 25.04 NA
## 65 NA 47.46 NA 22.05 NA
## 66 NA 65.69 NA 47.72 NA
## 67 NA 26.24 NA 24.98 NA
## 68 NA 63.58 NA 42.30 NA
## 69 NA 28.11 NA 40.85 NA
## 70 NA 2.99 NA 19.63 NA
## 71 NA 37.94 NA 43.87 NA
## 72 NA 4.43 NA 19.70 NA
## 73 NA 31.41 NA 30.35 NA
## 74 NA 16.89 NA 18.43 NA
## 75 NA 23.66 NA 37.68 NA
## 76 NA 15.75 NA 18.32 NA
## 77 NA 43.39 NA 32.77 NA
## 78 NA 30.22 NA 18.13 NA
## 79 NA 68.49 NA 33.81 NA
## 80 NA 56.48 NA 42.00 NA
## 81 NA 42.75 NA 21.23 NA
## 82 NA 47.44 NA 35.89 NA
## 83 NA 81.79 NA 31.37 NA
## 84 NA 27.88 NA 38.42 NA
## 85 NA 11.53 NA 31.41 NA
## 86 NA 31.90 NA 36.66 NA
## 87 NA 26.82 NA 29.02 NA
## 88 NA 33.39 NA 31.01 NA
## 89 NA 30.46 NA 29.60 NA
## 90 NA 2.19 NA 18.40 NA
## 91 NA 111.22 NA 58.74 NA
## 92 NA 514.85 NA 23.49 NA
## 93 NA 38.27 NA 27.16 NA
## 94 NA 10.30 NA 29.10 NA
## 95 NA 55.27 NA 66.30 NA
## 96 NA 4.50 NA 14.13 NA
## 97 NA 6.76 NA 28.46 NA
## 98 NA 15.61 NA 26.93 NA
## 99 NA 49.93 NA 16.08 NA
## 100 NA 54.66 NA 23.12 NA
## 101 NA 45.66 NA 30.78 NA
## 102 NA 36.95 NA 28.14 NA
## 103 NA 9.07 NA 19.76 NA
## 104 NA 42.30 NA 26.56 NA
## 105 NA 7.47 NA 34.26 NA
## 106 NA 30.20 NA 23.21 NA
## 107 NA 45.52 NA 40.61 NA
## 108 NA 49.59 NA 46.21 NA
## 109 NA 39.76 NA 25.51 NA
## 110 NA 8.36 NA 18.74 NA
## 111 NA 34.52 NA 47.12 NA
## 112 NA 11.45 NA 41.76 NA
## 113 NA 16.53 NA 20.90 NA
## 114 NA 56.12 NA 52.91 NA
## 115 NA 45.58 NA 20.72 NA
## 116 NA 10.99 NA 36.98 NA
## 117 NA 70.68 NA 17.90 NA
## 118 NA 22.10 NA 37.09 NA
## 119 NA 54.25 NA 37.68 NA
## 120 NA 43.28 NA 23.22 NA
## 121 NA 29.78 NA 21.19 NA
## 122 NA 47.40 NA 29.95 NA
## 123 NA 75.61 NA 69.14 NA
## 124 NA 9.15 NA 10.79 NA
## 125 NA 53.93 NA 22.52 NA
## 126 NA 15.86 NA 24.65 NA
## 127 NA 28.67 NA 27.63 NA
## 128 NA 104.66 NA 121.03 NA
## 129 NA 50.90 NA 36.54 NA
## 130 NA 38.66 NA 35.20 NA
## 131 NA 61.61 NA 11.30 NA
## 132 NA 221.97 NA 74.72 NA
## 133 NA 52.59 NA 35.98 NA
## 134 NA 29.66 NA 26.35 NA
## 135 NA 49.74 NA 34.15 NA
## 136 NA 35.17 NA 32.98 NA
## 137 NA 9.28 NA 24.16 NA
## 138 NA 19.49 NA 14.77 NA
## 139 NA 18.81 NA 38.65 NA
## 140 NA 41.42 NA 41.54 NA
## 141 NA 76.99 NA 44.40 NA
## 142 NA 30.38 NA 26.38 NA
## 143 NA 28.40 NA 24.59 NA
## 144 NA 122.73 NA 36.66 NA
## 145 NA 30.74 NA 37.71 NA
## 146 NA 37.42 NA 19.93 NA
## 147 NA 146.66 NA 43.12 NA
## 148 NA 39.41 NA 21.07 NA
## 149 NA 18.74 NA 27.07 NA
## 150 NA 13.38 NA 41.07 NA
## 151 NA 14.35 NA 18.48 NA
## 152 NA 51.31 NA 26.87 NA
## 153 NA 37.20 NA 100.34 NA
## 154 NA 39.51 NA 29.94 NA
## 155 NA 16.67 NA 41.88 NA
## 156 NA 35.33 NA 22.04 NA
## 157 NA 35.16 NA 28.81 NA
## 158 NA 22.20 NA 23.47 NA
## 159 NA 78.50 NA 48.32 NA
## 160 NA 9.50 NA 24.43 NA
## 161 NA 55.92 NA 30.58 NA
## 162 NA 46.80 NA 51.85 NA
## 163 NA 140.28 NA 119.31 NA
## 164 NA 50.32 NA 24.35 NA
## 165 NA 15.56 NA 26.78 NA
## 166 NA 90.50 NA 65.45 NA
## 167 NA 67.57 NA 204.59 NA
## 168 NA 102.00 NA 30.45 NA
## 169 NA 51.09 NA 39.59 NA
## 170 NA 50.29 NA 51.45 NA
## 171 NA 20.00 NA 21.25 NA
## 172 NA 18.43 NA 30.79 NA
## 173 NA 93.88 NA 33.99 NA
## 174 NA 28.31 NA 23.34 NA
## 175 NA 21.15 NA 14.92 NA
## 176 NA 32.84 NA 15.52 NA
## 177 NA 6.33 NA 10.24 NA
## 178 NA 15.54 NA 57.91 NA
## 179 NA 22.61 NA 11.66 NA
## 180 NA 46.08 NA 36.48 NA
## 181 NA 63.79 NA 20.42 NA
## 182 NA 38.73 NA 40.12 NA
## 183 NA 60.13 NA 46.70 NA
## 184 NA 50.71 NA 32.02 NA
## 185 NA 36.67 NA 28.19 NA
## 186 NA 14.15 NA 24.20 NA
## 187 NA 27.97 NA 15.07 NA
## 188 NA 21.97 NA 21.21 NA
## 189 NA 6.62 NA 16.66 NA
## 190 NA 16.29 NA 23.73 NA
## 191 NA 12.12 NA 23.45 NA
## 192 NA 33.30 NA 21.59 NA
## 193 NA 42.34 NA 24.38 NA
## 194 NA 39.79 NA 46.42 NA
## 195 NA 5.09 NA 53.83 NA
## 196 NA 41.74 NA 35.13 NA
## 197 NA 3.08 NA 11.76 NA
## groupTime7662 beamtreeTime groupTime7663 startreeTime groupTime7646 ENDTime
## 1 17.98 NA 18.63 NA 2.54 NA
## 2 17.88 NA 36.23 NA 2.60 NA
## 3 19.04 NA 31.38 NA 3.39 NA
## 4 17.56 NA 27.75 NA 2.87 NA
## 5 31.66 NA 22.00 NA 2.21 NA
## 6 75.57 NA 73.74 NA 3.41 NA
## 7 69.58 NA 35.93 NA 4.11 NA
## 8 33.32 NA 36.80 NA 7.86 NA
## 9 18.10 NA 32.01 NA 5.78 NA
## 10 33.52 NA 32.65 NA 3.07 NA
## 11 16.06 NA 23.94 NA 2.36 NA
## 12 41.49 NA 56.52 NA 4.01 NA
## 13 12.05 NA 18.08 NA 3.55 NA
## 14 46.84 NA 44.61 NA 7.28 NA
## 15 26.03 NA 36.55 NA 3.32 NA
## 16 16.61 NA 18.78 NA 2.11 NA
## 17 15.90 NA 23.60 NA 3.33 NA
## 18 20.94 NA 23.83 NA 3.47 NA
## 19 25.57 NA 21.07 NA 6.01 NA
## 20 21.87 NA 23.11 NA 3.15 NA
## 21 39.95 NA 39.95 NA 4.76 NA
## 22 8.26 NA 18.10 NA 2.72 NA
## 23 23.38 NA 31.34 NA 2.82 NA
## 24 16.94 NA 58.91 NA 4.76 NA
## 25 27.97 NA 32.94 NA 3.81 NA
## 26 27.59 NA 36.38 NA 3.22 NA
## 27 46.59 NA 30.35 NA 8.12 NA
## 28 38.10 NA 35.44 NA 4.36 NA
## 29 21.89 NA 24.96 NA 3.88 NA
## 30 36.53 NA 51.70 NA 12.21 NA
## 31 12.01 NA 46.47 NA 2.65 NA
## 32 44.43 NA 33.76 NA 3.96 NA
## 33 18.59 NA 82.83 NA 4.39 NA
## 34 32.86 NA 28.75 NA 9.27 NA
## 35 82.10 NA 70.51 NA 19.02 NA
## 36 30.66 NA 42.15 NA 2.44 NA
## 37 28.29 NA 19.90 NA 3.25 NA
## 38 26.73 NA 30.19 NA 3.62 NA
## 39 15.13 NA 18.58 NA 4.63 NA
## 40 32.57 NA 31.06 NA 2.52 NA
## 41 51.81 NA 48.01 NA 4.80 NA
## 42 14.16 NA 17.43 NA 3.21 NA
## 43 26.69 NA 35.43 NA 5.29 NA
## 44 28.75 NA 36.35 NA 136.05 NA
## 45 46.96 NA 387.36 NA 41.72 NA
## 46 13.79 NA 28.07 NA 2.85 NA
## 47 14.46 NA 11.58 NA 3.05 NA
## 48 61.63 NA 35.51 NA 81.02 NA
## 49 19.87 NA 18.23 NA 2.61 NA
## 50 22.85 NA 67.08 NA 3.16 NA
## 51 19.80 NA 24.59 NA 3.63 NA
## 52 38.10 NA 36.19 NA 3.36 NA
## 53 9.91 NA 23.69 NA 3.29 NA
## 54 24.85 NA 66.48 NA 2.83 NA
## 55 49.86 NA 52.12 NA 8.43 NA
## 56 33.35 NA 61.59 NA 4.13 NA
## 57 30.53 NA 29.82 NA 2.55 NA
## 58 28.74 NA 42.39 NA 2.65 NA
## 59 30.33 NA 51.91 NA 3.10 NA
## 60 24.09 NA 28.89 NA 8.07 NA
## 61 17.09 NA 27.50 NA 2.68 NA
## 62 33.59 NA 39.71 NA 3.25 NA
## 63 26.23 NA 74.33 NA 3.61 NA
## 64 41.36 NA 34.21 NA 22.39 NA
## 65 29.57 NA 41.66 NA 4.27 NA
## 66 43.64 NA 53.54 NA 3.26 NA
## 67 24.49 NA 25.84 NA 5.15 NA
## 68 25.61 NA 30.31 NA 2.54 NA
## 69 49.13 NA 84.42 NA 3.08 NA
## 70 12.07 NA 13.61 NA 6.38 NA
## 71 29.31 NA 30.02 NA 2.66 NA
## 72 18.57 NA 24.43 NA 2.86 NA
## 73 28.96 NA 25.24 NA 3.77 NA
## 74 24.96 NA 27.47 NA 2.96 NA
## 75 37.65 NA 61.96 NA 78.65 NA
## 76 33.50 NA 35.88 NA 3.00 NA
## 77 57.29 NA 55.62 NA 3.21 NA
## 78 45.18 NA 48.42 NA 2.17 NA
## 79 26.57 NA 27.26 NA 3.26 NA
## 80 51.87 NA 42.35 NA 4.14 NA
## 81 25.87 NA 28.94 NA 2.98 NA
## 82 44.16 NA 43.42 NA 14.59 NA
## 83 41.71 NA 84.02 NA 8.12 NA
## 84 21.66 NA 40.50 NA 4.78 NA
## 85 30.16 NA 42.99 NA 2.65 NA
## 86 34.02 NA 30.48 NA 3.73 NA
## 87 21.98 NA 36.47 NA 2.89 NA
## 88 25.17 NA 20.98 NA 8.60 NA
## 89 55.75 NA 54.25 NA 10.52 NA
## 90 15.24 NA 18.80 NA 1.89 NA
## 91 65.20 NA 62.25 NA 4.34 NA
## 92 41.86 NA 28.97 NA 3.76 NA
## 93 55.08 NA 23.18 NA 2.50 NA
## 94 30.72 NA 33.99 NA 2.15 NA
## 95 83.63 NA 55.93 NA 6.20 NA
## 96 9.82 NA 26.83 NA 3.06 NA
## 97 35.90 NA 53.34 NA 10.67 NA
## 98 21.68 NA 54.28 NA 2.72 NA
## 99 35.53 NA 23.89 NA 1.98 NA
## 100 9.75 NA 22.69 NA 3.18 NA
## 101 35.67 NA 26.86 NA 3.89 NA
## 102 31.47 NA 26.68 NA 2.92 NA
## 103 26.74 NA 34.11 NA 5.04 NA
## 104 30.27 NA 40.09 NA 4.76 NA
## 105 24.67 NA 32.21 NA 3.13 NA
## 106 30.88 NA 52.22 NA 4.55 NA
## 107 24.86 NA 46.63 NA 3.09 NA
## 108 58.26 NA 101.22 NA 13.77 NA
## 109 27.17 NA 31.18 NA 2.80 NA
## 110 35.58 NA 32.31 NA 3.00 NA
## 111 28.71 NA 47.38 NA 10.70 NA
## 112 33.23 NA 19.25 NA 3.38 NA
## 113 20.26 NA 33.98 NA 22.74 NA
## 114 75.14 NA 41.42 NA 9.25 NA
## 115 22.45 NA 28.27 NA 11.57 NA
## 116 18.12 NA 24.31 NA 2.73 NA
## 117 19.18 NA 31.04 NA 3.23 NA
## 118 15.97 NA 32.35 NA 3.07 NA
## 119 25.20 NA 45.11 NA 3.06 NA
## 120 26.30 NA 34.74 NA 2.42 NA
## 121 43.66 NA 13.41 NA 3.97 NA
## 122 20.27 NA 31.70 NA 4.08 NA
## 123 48.13 NA 60.58 NA 4.16 NA
## 124 14.44 NA 36.75 NA 3.12 NA
## 125 60.62 NA 33.50 NA 3.96 NA
## 126 27.21 NA 31.75 NA 3.09 NA
## 127 23.33 NA 35.21 NA 7.73 NA
## 128 164.74 NA 196.80 NA 2.82 NA
## 129 27.86 NA 34.49 NA 4.93 NA
## 130 31.81 NA 65.67 NA 4.60 NA
## 131 20.11 NA 27.18 NA 3.61 NA
## 132 83.33 NA 97.71 NA 15.02 NA
## 133 33.35 NA 49.12 NA 3.14 NA
## 134 22.23 NA 30.69 NA 4.21 NA
## 135 47.08 NA 33.43 NA 4.30 NA
## 136 51.34 NA 41.78 NA 3.30 NA
## 137 21.28 NA 24.00 NA 3.54 NA
## 138 13.82 NA 206.46 NA 3.11 NA
## 139 24.51 NA 14.85 NA 54.60 NA
## 140 27.98 NA 30.07 NA 3.11 NA
## 141 33.31 NA 57.21 NA 3.38 NA
## 142 16.30 NA 32.45 NA 41.84 NA
## 143 27.21 NA 27.47 NA 2.63 NA
## 144 36.15 NA 28.87 NA 3.95 NA
## 145 36.00 NA 33.57 NA 3.39 NA
## 146 32.29 NA 22.16 NA 3.32 NA
## 147 31.67 NA 104.88 NA 8.86 NA
## 148 22.44 NA 33.02 NA 2.74 NA
## 149 49.80 NA 33.56 NA 2.92 NA
## 150 34.59 NA 32.26 NA 4.01 NA
## 151 27.18 NA 68.15 NA 3.35 NA
## 152 53.14 NA 62.59 NA 2.50 NA
## 153 41.30 NA 48.43 NA 83.35 NA
## 154 37.92 NA 43.87 NA 4.45 NA
## 155 27.77 NA 32.42 NA 4.32 NA
## 156 21.31 NA 25.77 NA 2.96 NA
## 157 29.19 NA 29.96 NA 2.82 NA
## 158 28.03 NA 36.65 NA 4.97 NA
## 159 61.06 NA 41.75 NA 3.58 NA
## 160 22.42 NA 30.75 NA 3.94 NA
## 161 39.06 NA 54.65 NA 33.76 NA
## 162 22.80 NA 23.28 NA 3.89 NA
## 163 41.53 NA 63.16 NA 3.90 NA
## 164 35.21 NA 42.94 NA 3.43 NA
## 165 21.48 NA 24.01 NA 2.27 NA
## 166 125.32 NA 154.09 NA 5.80 NA
## 167 68.63 NA 51.92 NA 15.20 NA
## 168 30.68 NA 48.49 NA 4.67 NA
## 169 38.50 NA 56.33 NA 4.47 NA
## 170 79.97 NA 133.82 NA 17.83 NA
## 171 44.65 NA 33.43 NA 3.20 NA
## 172 28.20 NA 39.36 NA 2.33 NA
## 173 52.44 NA 121.76 NA 11.40 NA
## 174 17.15 NA 26.06 NA 4.84 NA
## 175 13.73 NA 33.15 NA 3.82 NA
## 176 23.08 NA 17.75 NA 29.18 NA
## 177 7.39 NA 738.74 NA 2.14 NA
## 178 10.45 NA 17.32 NA 3.96 NA
## 179 16.34 NA 12.02 NA 3.52 NA
## 180 17.94 NA 38.79 NA 4.03 NA
## 181 50.20 NA 142.17 NA 9.02 NA
## 182 48.59 NA 39.91 NA 4.19 NA
## 183 26.36 NA 35.32 NA 5.46 NA
## 184 28.60 NA 88.00 NA 3.10 NA
## 185 43.68 NA 59.12 NA 4.57 NA
## 186 23.08 NA 35.25 NA 3.02 NA
## 187 14.75 NA 18.10 NA 2.95 NA
## 188 28.49 NA 25.82 NA 3.57 NA
## 189 12.99 NA 21.72 NA 2.97 NA
## 190 17.07 NA 18.11 NA 3.00 NA
## 191 29.71 NA 22.78 NA 22.41 NA
## 192 31.98 NA 30.70 NA 3.94 NA
## 193 31.70 NA 44.72 NA 3.14 NA
## 194 57.62 NA 52.60 NA 5.81 NA
## 195 74.16 NA 16.39 NA 2.87 NA
## 196 18.49 NA 33.17 NA 3.44 NA
## 197 8.58 NA 10.56 NA 12.98 NA
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# split data
# results for Sunburst - our scale
data_sun <- data[, c('sunburst.enjoyable.', 'sunburst.likable.', 'sunburst.pleasing.', 'sunburst.nice.', 'sunburst.appealing.')]
# results for Sunburst - classic aesthetic for website scale
data_sun_ca <- data[, c('sunburst.aesthetic.', 'sunburst.pleasant.', 'sunburst.clear.', 'sunburst.clean.', 'sunburst.symmetric.')]
# results for Beamtree - our scale
data_beam <- data[, c('beamtree.enjoyable.', 'beamtree.likable.', 'beamtree.pleasing.', 'beamtree.nice.', 'beamtree.appealing.')]
# results for Beamtree - classic aesthetic for website scale
data_beam_ca <- data[, c('beamtree.aesthetic.', 'beamtree.pleasant.', 'beamtree.clear.', 'beamtree.clean.', 'beamtree.symmetric.')]
# results for Startree - our scale
data_star <- data[, c('startree.enjoyable.', 'startree.likable.', 'startree.pleasing.', 'startree.nice.', 'startree.appealing.')]
# results for Startree - classic aesthetic for website scale
data_star_ca <- data[, c('startree.aesthetic.', 'startree.pleasant.', 'startree.clear.', 'startree.clean.', 'startree.symmetric.')]
#Clean the column name function
cleanColnames <- function(data, visName){
# delete visName and . from column name of dataframe, only keep the terms as column name
names(data) <- sub(paste(visName, ".", sep =""), "", names(data))
names(data) <- sub("\\.", "", names(data))
return(data)
}
# Clean column names for all data
data_sun <- cleanColnames(data_sun, "sunburst")
data_sun_ca <- cleanColnames(data_sun_ca, "sunburst")
data_beam <- cleanColnames(data_beam, "beamtree")
data_beam_ca <- cleanColnames(data_beam_ca, "beamtree")
data_star <- cleanColnames(data_star, "startree")
data_star_ca <- cleanColnames(data_star_ca, "startree")
CFA <- function(data){
APV.model ='aesthetic_pleasure =~ enjoyable + likable + pleasing + nice + appealing'
fit <- cfa(APV.model,data = data,std.lv = TRUE)
pvalue <- fitMeasures(fit, "pvalue")
tli <- fitMeasures(fit, "tli")
cfi <- fitMeasures(fit, "cfi")
srmr <- fitMeasures(fit, "srmr")
rmsea <- fitMeasures(fit, "rmsea")
good_fit_list <- NULL
good_fit_list <- c(pvalue, tli, cfi, srmr, rmsea)
summary(fit, fit.measures=T, standardized=TRUE)
return(good_fit_list)
}
#CFA factor numbers
APV.model ='aesthetic_pleasure =~ enjoyable + likable + pleasing + nice + appealing'
fit1 <- cfa(APV.model,data = data_sun,std.lv = TRUE)
l1 <- lavInspect(fit1, what = "std.all", add.labels = TRUE, add.class = TRUE,
list.by.group = TRUE,
drop.list.single.group = TRUE)[[1]]
fit2 <- cfa(APV.model,data = data_star,std.lv = TRUE)
l2 <- lavInspect(fit2, what = "std.all", add.labels = TRUE, add.class = TRUE,
list.by.group = TRUE,
drop.list.single.group = TRUE)[[1]]
fit3 <- cfa(APV.model,data = data_beam,std.lv = TRUE)
l3 <- lavInspect(fit3, what = "std.all", add.labels = TRUE, add.class = TRUE,
list.by.group = TRUE,
drop.list.single.group = TRUE)[[1]]
df_factor_loading_cfa <- cbind(l1, l2, l3)
df_factor_loading_cfa
## aesthetic_pleasure aesthetic_pleasure aesthetic_pleasure
## enjoyable 0.8934088 0.8776919 0.9108554
## likable 0.9142477 0.9245434 0.8739083
## pleasing 0.8888896 0.8948153 0.8926274
## nice 0.8452368 0.8772203 0.8876559
## appealing 0.9096641 0.8423809 0.8889816
good_fit_sun <- CFA(data_sun)
good_fit_star <- CFA(data_star)
good_fit_beam <- CFA(data_beam)
good_fit_table <- cbind(good_fit_sun, good_fit_star, good_fit_beam)
good_fit_table
## good_fit_sun good_fit_star good_fit_beam
## pvalue 0.289999205 0.22164625 0.01604389
## tli 0.997580176 0.99571328 0.98156124
## cfi 0.998790088 0.99785664 0.99078062
## srmr 0.009135926 0.01055442 0.01353385
## rmsea 0.034469107 0.04490826 0.09522884
con_vali <- function(data1, data2){ # results of two scales you want to calculate correlation
cor.test(rowMeans(data1), rowMeans(data2), method = "pearson")
}
dis_vali <- function(data1){ # result of your scale
cor.test(rowMeans(data1), data$age , method = "pearson")
}
CFA(data_sun)
## pvalue tli cfi srmr rmsea
## 0.289999205 0.997580176 0.998790088 0.009135926 0.034469107
con_vali(data_sun, data_sun_ca)
##
## Pearson's product-moment correlation
##
## data: rowMeans(data1) and rowMeans(data2)
## t = 21.454, df = 195, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.7909840 0.8753427
## sample estimates:
## cor
## 0.8381053
dis_vali(data_sun)
##
## Pearson's product-moment correlation
##
## data: rowMeans(data1) and data$age
## t = 1.033, df = 194, p-value = 0.3029
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.06688702 0.21191501
## sample estimates:
## cor
## 0.07395897
cronbach.alpha(data_sun)
##
## Cronbach's alpha for the 'data_sun' data-set
##
## Items: 5
## Sample units: 197
## alpha: 0.95
CFA(data_star)
## pvalue tli cfi srmr rmsea
## 0.22164625 0.99571328 0.99785664 0.01055442 0.04490826
con_vali(data_star, data_star_ca)
##
## Pearson's product-moment correlation
##
## data: rowMeans(data1) and rowMeans(data2)
## t = 25.384, df = 195, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.8391602 0.9051052
## sample estimates:
## cor
## 0.8761713
dis_vali(data_star)
##
## Pearson's product-moment correlation
##
## data: rowMeans(data1) and data$age
## t = 1.6617, df = 194, p-value = 0.09818
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.02205285 0.25439483
## sample estimates:
## cor
## 0.118466
cronbach.alpha(data_star)
##
## Cronbach's alpha for the 'data_star' data-set
##
## Items: 5
## Sample units: 197
## alpha: 0.946
CFA(data_beam)
## pvalue tli cfi srmr rmsea
## 0.01604389 0.98156124 0.99078062 0.01353385 0.09522884
con_vali(data_beam, data_beam_ca)
##
## Pearson's product-moment correlation
##
## data: rowMeans(data1) and rowMeans(data2)
## t = 24.339, df = 195, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.8279820 0.8982566
## sample estimates:
## cor
## 0.8673799
dis_vali(data_beam)
##
## Pearson's product-moment correlation
##
## data: rowMeans(data1) and data$age
## t = 1.9826, df = 194, p-value = 0.04882
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.0007843402 0.2756303317
## sample estimates:
## cor
## 0.1409215
cronbach.alpha(data_beam)
##
## Cronbach's alpha for the 'data_beam' data-set
##
## Items: 5
## Sample units: 197
## alpha: 0.95
#Cronbach's Alpha for CFA
df_alpha <- data.frame(matrix(ncol = 3, nrow = 0))
list_alpha <- c(cronbach.alpha(data_sun)$alpha, cronbach.alpha(data_star)$alpha,cronbach.alpha(data_beam)$alpha)
colnames(df_alpha) <- c("SunBurst", "StarTree", "BeamTree")
df_alpha[nrow(df_alpha) + 1,] <- list_alpha
row.names(df_alpha) <- "Cronbach’s Alpha"
df_alpha <- df_alpha %>%
mutate_if(is.numeric, round, digits=2)
df_alpha
## SunBurst StarTree BeamTree
## Cronbach’s Alpha 0.95 0.95 0.95
write.table(df_alpha, paste("results/cfa_alpha.tsv",sep=""),row.names=TRUE,col.names=NA,sep='\t')
# Pearson correlation
df_pearson <- data.frame(matrix(ncol = 3, nrow = 0))
list_pearson_con <- c(con_vali(data_sun, data_sun_ca)$estimate,con_vali(data_star, data_star_ca)$estimate,con_vali(data_beam, data_beam_ca)$estimate)
list_pearson_dis <- c(dis_vali(data_sun)$estimate,dis_vali(data_star)$estimate,dis_vali(data_beam)$estimate)
colnames(df_pearson) <- c("SunBurst", "StarTree", "BeamTree")
df_pearson[nrow(df_pearson) + 1,] <- list_pearson_con
df_pearson[nrow(df_pearson) + 1,] <- list_pearson_dis
row.names(df_pearson) <- c("Classic Aesthetic", "Age")
df_pearson <- df_pearson %>%
mutate_if(is.numeric, round, digits=2)
df_pearson
## SunBurst StarTree BeamTree
## Classic Aesthetic 0.84 0.88 0.87
## Age 0.07 0.12 0.14
write.table(df_pearson, paste("results/cfa_pearson.tsv",sep=""),row.names=TRUE,col.names=NA,sep='\t')
This code calculates the average ratings each image received from participants and saves them as plots with CIs.
source("04_CFA/CI-Functions.R")
participantResponseFiles <- list.files(path= "04_CFA/data",pattern = "\\.csv$") #names correspond to images, one participant per row, one word per
This one cleans up the column names for each image’s responses
cleanColnames <- function(data){
newNames <- gsub("^.+?\\.(.+?)\\..*$", "\\1", colnames(data))
return(newNames)
}
This functions draws a bar chart with confidence intervals
barChart <- function(resultTable, techniques, nbTechs = -1, ymin, ymax, xAxisLabel = "I am the X axis", yAxisLabel = "I am the Y Label",plotTitle){
#tr <- t(resultTable)
if(nbTechs <= 0){
stop('Please give a positive number of Techniques, nbTechs');
}
tr <- as.data.frame(resultTable)
nbTechs <- nbTechs - 1 ; # seq will generate nb+1
#now need to calculate one number for the width of the interval
tr$CI2 <- tr$upperBound_CI - tr$mean
tr$CI1 <- tr$mean - tr$lowerBound_CI
#add a technique column
tr$technique <- factor(seq.int(0, nbTechs, 1));
breaks <- c(as.character(tr$technique));
print(tr)
g <- ggplot(tr, aes(x=technique, y=mean)) +
# geom_bar(stat="identity",fill = I("#CCCCCC")) +
geom_errorbar(aes(ymin=mean-CI1, ymax=mean+CI2),
width=0, # Width of the error bars
size = 1.1
) +
#labs(title="Overall time per technique") +
labs(x = xAxisLabel, y = yAxisLabel) +
scale_y_continuous(limits = c(ymin,ymax),breaks=1:7) +
scale_x_discrete(name="",breaks,techniques)+
coord_flip() +
ggtitle(plotTitle) +
theme(panel.background = element_rect(fill = 'white', colour = 'white'),axis.title=element_text(size = rel(1.2), colour = "black"),axis.text=element_text(size = rel(1.2), colour = "black"),panel.grid.major = element_line(colour = "#DDDDDD"),panel.grid.major.y = element_blank(), panel.grid.minor.y = element_blank())+
geom_point(size=2, colour="black") # dots
print(g)
}
This next function calculates the CIs of each image’s responses depending on the scale items (terms) given.
calculateDrawResponseCIs <- function(scaleItems){
imageCount <- length(participantResponseFiles)
pointEstimateVector = c()
lowerBoundVector = c()
upperBoundVector = c()
imageVector = c()
for (image in 1:imageCount){
data <- read.csv(paste("04_CFA/data/",participantResponseFiles[[image]],sep=""), encoding="UTF-8")
#terms <- cleanColnames(data)
#colnames(data) <- terms
#exploratory trying to see what would happen if we had had a lot fewer participants
#data <- data[sample(nrow(data), 24), ]
data <- data[scaleItems]
means <- rowMeans(data)
imageVector <- append(imageVector,image)
ci <- bootstrapMeanCI(means)
pointEstimateVector <- append(pointEstimateVector,ci[1])
upperBoundVector <- append(upperBoundVector,ci[3])
lowerBoundVector <- append(lowerBoundVector,ci[2])
}
df <- data.frame(image=imageVector,mean=pointEstimateVector,lowerBound_CI=lowerBoundVector,upperBound_CI=upperBoundVector)
plotTitle <- paste(paste("Average Rating for the",length(scaleItems)),"item scale")
barChart(df,df$image ,nbTechs = imageCount, ymin = 1, ymax = 7, "Image", "Average Ratings",plotTitle)
ggsave(paste("results/",paste(plotTitle,".pdf",sep=""),sep=""), width=8, height=4,device=cairo_pdf)
print(df)
return(df)
}
As the ratings per image were done by different participant pools we don’t actually want to compare the ratings of each image.
generatePerImageTables <-function(dfs,titles){
imageCounts <- length(participantResponseFiles)
for(i in 1:imageCounts){
pointEstimateVector = c()
lowerBoundVector = c()
upperBoundVector = c()
scaleVector = c()
dflength <- length(dfs)
for(d in 1:dflength){
scaleVector <- append(scaleVector,titles[d])
df <- dfs[[d]]
pointEstimateVector <- append(pointEstimateVector,df$mean[df$image==i])
upperBoundVector <- append(upperBoundVector,df$upperBound_CI[df$image==i])
lowerBoundVector <- append(lowerBoundVector,df$lowerBound_CI[df$image==i])
}
df <- data.frame(scale=scaleVector,mean=pointEstimateVector,lowerBound_CI=lowerBoundVector,upperBound_CI=upperBoundVector)
plotTitle <- paste(paste("Image",i)," Ratings Per Scale")
barChart(df,df$scale ,nbTechs = dflength, ymin = 1, ymax = 7, "Image", "Average Ratings",plotTitle)
path<-paste("results/",paste(plotTitle,".pdf",sep=""),sep="")
print(path)
ggsave(path, width=8, height=4,device=cairo_pdf)
}
}
And now we run our tests
data <- read.csv(paste("04_CFA/data/",participantResponseFiles[[1]],sep=""), encoding="UTF-8")
scaleItems <- colnames(data)
scaleItems
## [1] "enjoyable" "likable" "pleasing" "nice" "appealing"
df31 <- calculateDrawResponseCIs(scaleItems)
## image mean lowerBound_CI upperBound_CI CI2 CI1 technique
## 1 1 3.019289 2.820305 3.220305 0.2010152 0.1989848 0
## 2 2 3.824365 3.621320 4.019289 0.1949239 0.2030457 1
## 3 3 4.396954 4.203046 4.578268 0.1813133 0.1939086 2
## image mean lowerBound_CI upperBound_CI
## 1 1 3.019289 2.820305 3.220305
## 2 2 3.824365 3.621320 4.019289
## 3 3 4.396954 4.203046 4.578268